MILOVANOVIC IVAN (IE)
GARGAN CAOIMHE (IE)
WO2008011179A2 | 2008-01-24 |
CN105777865B | 2020-07-28 | |||
CN104558114A | 2015-04-29 | |||
EP1493440A1 | 2005-01-05 | |||
CN105063150A | 2015-11-18 | |||
US20160144005A1 | 2016-05-26 |
Claims 1. A method for producing a marine peptide product from a marine by-product derived from fish processing, the method comprising: filtering a marine by-product, wherein the marine by-product is (i) blue whiting or mackerel bloodwater, or (ii) one or more of fish skins, fish bone and gut waste from blue whiting or mackerel, using one or more filters selected from 3kDa filter membrane and 10kDa filter membrane, to obtain at least one retentate, a 3kDa fraction and/or a 10kDa fraction, wherein the marine peptide product is the obtained fraction(s). 2. The method of Claim 1, further comprising a step of drying the at least one retentate, 10kDa fraction and/or 3kDa fraction. 3. The method of Claim 1 or 2, wherein the by-product is bloodwater from blue whiting or mackerel. 4. The method of Claim 1 or 2, wherein the by-product is one or more of fish skins, fish bone, and gut waste from blue whiting or mackerel. 5. The method of Claim 4, wherein the by-product is one or more of fish skins, fish bone, and gut waste from blue whiting. 6. The method of Claim 4 or 5, wherein the method comprises a step of extracting gelatine from the by-product to provide a by-product in the form of a gelatine extract, prior to filtering. 7. The method of Claim 4 to 6, wherein the method comprises a step of hydrolysing the by-product, or the gelatine extract, with one or more hydrolysis enzymes prior to filtering. 8. The method of Claim 7, wherein the enzymes are alcalase or papain. 9. A method for producing a marine peptide product from a mackerel by-product derived from fish processing, the method comprising: hydrolysing the mackerel by-product, which is one or more of fish skins, fish bone and gut waste, with one or more hydrolysis enzymes selected from alcalase and papain, using one or more filters selected from 3kDa filter membrane and 10kDa filter membrane, to obtain at least one retentate, a 3kDa fraction and/or a 10kDa fraction, wherein the marine peptide product is the obtained fraction(s). 10. The method of Claim 9, wherein the method comprises an initial step of extracting gelatine from the mackerel by-product prior to hydrolysing to provide a mackerel by-product in the form of a gelatine extract. 11. A marine peptide product obtained from the method of any one of Claims 1 to 10. 12. A marine peptide product obtained from the method of any one of Claims 4 to 10, wherein the product is the 3kDa fraction. 13. A marine peptide product obtained from the method of any one of Claims 1 to 3, wherein the product is a 10kDa fraction. 14. A marine peptide product comprising one or more peptides selected from peptides comprising SEQUENCE ID NO.1 to SEQUENCE ID NO.64. 15. The marine peptide product of Claim 14, comprising all the peptides selected from the peptides comprising SEQUENCE ID NO.1 to SEQUENCE ID NO.64. 16. The marine peptide product of Claims 14 or 15, wherein the peptides consist of a sequence selected from SEQUENCE ID NO.1 to SEQUENCE ID NO.64. 17. A marine peptide product comprising one or more peptides selected from peptides comprising SEQUENCE ID NO.65 to SEQUENCE ID NO.169. 18. The marine peptide product of Claim 17, comprising all the peptides selected form peptides comprising SEQUENCE ID NO.65 to SEQUENCE ID NO.169. 19. The marine peptide product of Claims 17 or 18, wherein the peptides consist of a sequence selected from SEQUENCE ID NO.65 to SEQUENCE ID NO.169. 20. A marine peptide product comprising one or more peptides selected from peptides comprising SEQUENCE ID NO.170 to SEQUENCE ID NO.188. 21. The marine peptide product of Claim 20, comprising all the peptides selected from peptides comprising SEQUENCE ID NO.170 to SEQUENCE ID NO.188. 22. The marine peptide product of Claims 20 or 21, wherein the peptides consist of a sequence selected from SEQUENCE ID NO.170 to SEQUENCE ID NO.188. 23. A marine peptide product comprising one or more peptides selected from peptides comprising SEQUENCE ID NO.189 to SEQUENCE ID NO.271 and SEQUENCE 363.. 24. The marine peptide product of Claim 23, comprising all the peptides selected from peptides comprising SEQUENCE ID NO. 189 to SEQUENCE ID NO. 271 and SEQUENCE 363. 25. The marine peptide product of Claims 23 or 24, wherein the peptides consist of a sequence selected from SEQUENCE ID NO.189 to SEQUENCE ID NO.271 and SEQUENCE 363. 26. A marine peptide product comprising one or more peptides selected from peptides comprising SEQUENCE ID NO.272 to SEQUENCE ID NO.362. 27. The marine peptide product of Claim 26, comprising all the peptides selected from peptides comprising SEQUENCE ID NO.272 to SEQUENCE ID NO.362. 28. The marine peptide product of Claims 26 or 27, wherein the peptides consist of a sequence selected from SEQUENCE ID NO.272 to SEQUENCE ID NO.362. 30. A peptide comprising a sequence selected from SEQUENCE ID NO.1 to SEQUENCE ID NO.363, or an ACE-1 inhibitory variant thereof having 1 to 3 amino acid changes, wherein said the or each amino acid change is selected from an insertion deletion, addition, and substitution. 31. The peptide of Claim 30, wherein the peptide comprises a sequence selected from SEQUENCE ID NO.1 to 188 or an ACE-1 inhibitory variant thereof having 1 to 3 amino acid changes, wherein said the or each change is selected from an insertion, deletion, addition, and substitution. 32. The peptide of Claim 31, wherein the peptide consists of a sequence selected from SEQUENCE ID NO.1 to 188. 33. The peptide of Claim 30, wherein the peptide comprises a sequence selected from SEQUENCE ID NO.1, 2, 10, 13, 16, 22, 25, 32, 44, 57, 58, 64 and 62, or an ACE-1 inhibitory variant thereof having 1 to 3 amino acid changes, wherein said the or each amino acid change is selected from an insertion deletion, addition, and substitution. 34. The peptide of Claim 33, wherein the peptide consists of a sequence selected from SEQUENCE ID NO.1, 2, 10, 13, 16, 22, 25, 32, 44, 57, 58, 64 and 62. 35. The peptide of Claim 30, wherein the peptide comprises a sequence selected from SEQUENCE ID NO.122, 123, 133, 139, 141, 147, 148, 150, 152, 157 and 160 or an ACE-1 inhibitory variant thereof having 1 to 3 amino acid changes, wherein said the or each amino acid change is selected from an insertion deletion, addition, and substitution. 36. The peptide of Claim 35, wherein the peptide consists of a sequence selected from SEQUENCE ID NO.122, 123, 133, 139, 141, 147, 148, 150, 152, 157 and 160. 37. The peptide of Claim 30, wherein the peptide comprises a sequence selected from SEQUENCE ID NO 170, 171, 178, 182, 183, 187, 185, 184 and 186 or an ACE-1 inhibitory variant thereof having 1 to 3 amino acid changes, wherein said the or each change is selected from an insertion, deletion, addition, and substitution. 38. The peptide of Claim 37, wherein the peptide consists of a sequence selected from SEQUENCE ID NO.170, 171, 178, 182, 183, 187, 185, 184 and 186. 39. The marine peptide product of any one of Claims 14 to 28 further comprising at least one fatty acids. 40. The marine peptide product of Claim 39, wherein the at least one fatty acid is one or more of the fatty acids of Table 5. 41. An animal food product comprising the marine peptide product of any one of Claims 11 to 28 or 39 to 40 or a peptide of any one of Claims 30 to 38. 42. The animal food product of Claim 41, wherein the marine peptide product is the product of any one of Claims 11 to 28 or 39 to 40. 43. The animal food product of Claim 41 or 42, wherein the animal is a companion animal. 44. The animal food product of Claim 43, wherein the animal is a cat or a dog. 45. A marine peptide product of any one of Claims 11 to 28 or 39 to 40, a peptide of any one of Claims 30 to 38, or an animal food product of Claim 41 to 44, for use as a medicament in an animal. 46. A marine peptide product of any one of Claims 11 to 28 or 39 to 40, a peptide of any one of Claims 30 to 38, or an animal food product of Claim 41 to 44, for use in a method of treating or preventing a disease or condition selected from the group comprising heart disease, renal disease, inflammatory disease or condition, eye disease, high blood pressure and hypertension in an animal. 47. The marine peptide product, peptide, or animal food product for use of Claim 46, wherein the disease or condition is selected from the group comprising heart disease, renal disease, inflammatory disease or condition, eye disease, high blood pressure and hypertension. 48. The marine peptide product, peptide, or animal food product for use of Claim 47, wherein the method is for preventing or treating hypertension in an animal. 49. The marine peptide product, peptide, or animal food product for use of Claim 48, wherein the animal is an elderly dog. 50. The marine peptide product of Claim 12, or an animal food product comprising the marine peptide product of Claim 12, for use in a method of preventing or treating hypertension in an elderly dog. |
Table 1: Amino Acids The levels of taurine in fish bloodwater fractions analysed in BBPP were between 0.2 to 2 g/100g, which is considerably high compared to beef and pork muscle with taurine content of 50-100 mg/100g and 118 mg/100g, respectively. A variety of studies have identified the beneficial effects of taurine in the treatment of cardiovascular diseases, renal dysfunction, and retinal neuron damage and these bloodwaters could be useful in the development of complementary pet foods such as treats to enhance taurine levels for improved heart heath and renal function.”. A still further aspect provides a food product, or comestible product, comprising the marine peptide product obtained by the method of the invention. The food product is preferably a biscuit for consumption by a dog or cat. The biscuit may be any colour or shape. An aspect of the invention provides a marine peptide product or food product of the invention, for use in a method of treatment or prevention of disease in an animal, typically prevention. As shown in the accompanying examples, the marine peptide product of the invention has ACE-1 inhibition activity. The marine peptide product also has Renin inhibition activity. Therefore, it has an application for prevention or treatment of heart disease or renal disease in animals, particularly cats and dogs. The food product of the invention is intended as a functional food product and could be used as an alternative to traditional drugs or medicine. Notably, the current invention provides the use to treat or prevent hypertension in elderly animal, preferably dogs. Typically, this may be hypertension that has resulted from obesity, inflammation and/or proteinuria in the animal. In dogs with marked proteinuria ACE-1 inhibitors may also have reno-protective effects and reduce the magnitude of proteinuria. A method of treatment or prevention of a disease in an animal is also provided by the current invention comprising administration of the peptide product or peptide of the current invention to an animal. The disease may be selected from the group comprising heart disease and renal disease or an inflammatory disease or condition. The condition may be high blood pressure or hypertension or proteinuria. The heart disease may be selected from the group comprising, but not limited to, chronic heart failure (CHF), chronic valvular disease, hypertrophic cardiomyopathy, mitral valve regurgitation (MR), e.g., secondary to degeneration of the mitral valve apparatus, one associated with a metabolic syndrome, for examples, heart health or congestive heart failure and chronic renal failure (CRF). It will be appreciated that other ingredients or additives may be added to the food product of the invention. For example, an aroma enhancing ingredient, e.g. Fats (fish derived or tallow) can be added for aroma enhancement. Unlike conventional biscuit formulas, no salt is added in the most preferred embodiments of this invention. This embodiment of the invention provides higher quality protein or essential amino acids compared to traditional wheat flour biscuits. The total protein content of the biscuit embodiments can be selectively adjusted to provide eye health (cats) or heart health (dogs) benefits. Also provided is a method for producing a marine peptide product from a mackerel by-product derived from fish processing, the method comprising: hydrolysing the mackerel by-product, which is one or more of fish skins, fish bone and gut waste, with one or more hydrolyses enzymes selected from alcalase and papain, using one or more filters selected from 3kDa filter membrane and 10kDa filter membrane, to obtain at least one retentate, a 3kDa fraction and/or a 10kDa fraction, wherein the marine peptide product is the obtained fraction(s). The invention will now be described with reference to the following examples. EXAMPLES EXAMPLE 1: BLOODWATERS FROM PELAGIC FISH PROCESSING Sampling and stabilisation of pelagic blood-waters One litre (1 L) X 3 samples of either Refrigerated seawater (RSW) from the supply tanker, hopper or process-line containing fish blood from Mackerel, Blue-whiting or Horse mackerel were collected independently from five different processors (Table 2) during the period September-April 2016-2017. Samples were collected in 1 L bottles and transported immediately to the laboratory on ice where they were frozen at -80˚C and subsequently freeze- dried using an industrial scale FD 80 model freeze-drier (Cuddon Engineering, New Zealand), milled and stored at -20˚C until further use. The dry matter content of the samples was calculated following drying. The pH of the samples was determined at 20˚C using pH standard pH meter and a calibrated Hamilton double pore electrode. Up-scaled Fractionation of bloodwaters using molecular weight cut off filtration (MWCO) Skid system The concentration SKID (FDT engineering, Ireland) shown in Figure 1 and fitted with 3kDa and 10 kDa UF Koch membranes (Millipore, Cork, Ireland) was used for pilot scale concentration of blood-waters collected from the hopper during processing of Mackerel and Blue-whiting independently. Blue-whiting and mackerel blood waters were collected in 600 L containers in Killybegs in April 2018, frozen for 24 hrs and transported to the Teagasc Food Research Centre Ashtown where they were passed through the concentration SKID to produce retentate and permeate products (Figure 1). The flow rate was 37.5 L per hr and 600 L were processed in a 4 hr time period. The 3 and 10 kDa permeates and retentates produced were blast frozen for 30 mins and subsequently freeze-dried as previously described. Dry weight yields were calculated, and products stored at -80˚C until further analysis. Total protein and polypeptide profile The total protein content of all samples was analysed using the Bicinchoninic Acid Assay (BCA assay) using bovine serum albumin as a standard. In addition, proximate analysis was used to quantify protein, ash and lipid content of the samples. The total protein content was determined in triplicate using a LECO FP628 Protein analyser (LECO Corp., MI, USA) based on the Dumas method and according to AOAC method 992.15, 1990. The conversion factor of 6.25 was used to convert total nitrogen to protein. The total protein content and yields were calculated per litre of blood and are shown in Figure 14. Moisture and ash content were determined gravimetrically in accordance with previously described methods (Kolar 1992). Physical and chemical properties determination of blood water fractions Proximate analysis The yield of stabilized products was calculated after freeze-drying and weighing of the samples and is expressed as a percentage of the product in total mass of initial blood water. The total protein content of the samples was determined using the Dumas combustion method using a LECO FP328 Protein analyser (LECO Corp, MI USA), according to Association of Official Analytical Chemists (AOAC) method 992.15 (AOAC, 1990). The conversion factor of 6.25 was used to convert total nitrogen to protein. The ash content was determined gravimetrically, as previously described (Kolar, 1992). The total fat content was determined gravimetrically using Ankom XT15 Extractor (Ankom Technology, Macedon NY, USA) for lipid extraction, after previous acid hydrolysis using Ankom HCI Hydrolysis System according to manufacturers’ operating manual. Water activity Water activity (aw) of all samples was measured using an AquaLab Lite meter (Decagon Devices Inc., Germany). Approximately 0.25 g of finely powdered sample was placed in the water activity metre and aw and the temperature was recorded. Total and Amino Acid (TAA) analysis of samples For total amino acid composition analysis, recovered blood-water samples were hydrolyzed in 6M HCl at 110°C for 23 hours following the method of Hill (1965). Samples were then de- proteinised by mixing equal volumes of 24% (w/v) tri-chloroacetic acid (TCA) and sample, these were allowed to stand for 10 minutes before centrifuging at 14400 x g (Microcentaur, MSE, UK) for 10 minutes. Supernatants were removed and diluted with 0.2 M sodium citrate buffer, pH 2.2 to give approximately 250 nmol of each amino acid residue. Samples were then diluted 1 in 2 with the internal standard norleucine, to give a final concentration of 125 nm/mL. Amino acids were quantified using a Jeol JLC-500/V amino acid analyser (Jeol (UK) Ltd., Garden city, Herts, UK) fitted with a Jeol Na+ 133 high performance cation exchange column. Fatty acid methyl ester (FAME) analysis Lipids from samples of Blue whiting and Mackerel 3 KDa and 10 KDa permeates and retentates were extracted using ethanol and ethyl acetate mixture (1:1, w/w), as described by Lin et al. (2004). Extracted lipids were then directly converted to FAMEs using boron-trichloride in methanol (14%, w/v) without previous derivatization, with slight modifications of the method previously described by Araujo et al. (2008). Separation and analysis of the FAMEs was done using Agilent 7890A/5975C GC-MSD system (Agilent Technologies, Santa Clara, CA, USA) equipped with Agilent J&W DB-FastFAME column (30 m × 0.25 mm, 0.25 µm). Slightly modified method from Agilent Application note 5991-8706EN was used for analysis (Zou and Wu, 2018). Hydrogen was used as carrier gas in constant pressure mode at 8 PSI and sample injection volume was 1 µL in inlet split mode (25:1). Temperature program of oven was as follows: 50 °C (0.5 minutes), then 15 °C/min to 194 °C (4 minutes) and finally 4 °C/min to 240 °C (1 minute). Mass spectra were acquired in scan mode in the 40-550 AMU mass range. Chromatographic peaks (total ion chromatogram, TIC) were identified by comparison of retention times (RT) and mass spectra with peaks of analysed FAMEs in the standard mixture. Identification was confirmed by searching the generated MS spectra within available spectral database (NIST11) using Agilent ChemStation software (v X.XX). Supelco Fame 37 mix (Sigma Aldrich, Darmstadt, Germany) was utilized for external calibration by making series of appropriate dilutions with hexane, with individual compound peaks used to construct a five- point calibration curve. Each individual FAME is quantified by measuring response (peak area after integration) of a selected quantifier ion from the compound spectrum using ChemStation software.1 ml of glyceryl-tri-heptadecanoate (Sigma Aldrich, Darmstadt, Germany) in hexane (1 mg/ml, w/v) was added to lipid samples prior to derivatization, to correct for transesterification efficiency and procedural losses. All samples were analysed in triplicates and results expressed as concentration (mg/g) of each fatty acid in extracted fat. Determination of techno-functional properties Water and oil holding capacities The water holding capacity (WHC) and oil holding capacity (OHC) were measured using the modified methods described by Garcia-Vaquero et al. (2017). In brief, 100 mg of each fraction sample was mixed with 1 ml of distilled water or oil (olive and sunflower oil) using a vortex mixer (VV3, VWR International Ltd., Ireland) for 30 seconds. The suspension was then centrifuged at 2200 × g for 30 min (Eppendorf MiniSpin, Eppendorf UK Limited, United Kingdom) at 19 °C. The supernatant was then decanted by draining the tubes at 45° angle for 10 min (20 min for oil). Water/oil holding capacity was calculated by dividing the weight of water/oil absorbed by the weight of the protein sample and expressed as grams of water or sunflower oil held by 1 g of protein. Solubility Solubility in water (S) was determined using the modified method by Ogunwolu et al. (2009). 100 mg of each sample was dispersed in 10 ml deionised water. Using pH-meter, the pH of the dispersions was adjusted to 2, 4, 6, 8 and 10 with 0.1 N HCl and 0.1 N NaOH. The mixture was vortexed at room temperature (19-20 °C) for 5 min, and subsequently centrifuged at 7500 × g for 15 min (Lynx 6000, Thermo Fisher Scientific, MA USA). The protein content in the supernatant was determined using the Pierce™ BCA Protein Assay Kit (Thermo Fischer Scientific, MA, USA). Solubility of samples at different pH conditions was then calculated as: S (%) = (protein content in the supernatant/protein content in full dispersion) x 100. Foaming capacity The foaming capacity (FC) of the blood water permeates and retentate samples were determined by the modified method described by Garcia-Vaquero et al. (2017). Samples were suspended in deionized water to make 1% concentration (w/v) and the pH was adjusted to 2, 4, 6, 8 and 10 with 0.1 N HCl and 0.1 N NaOH. The suspensions were homogenized using a T 25 digital ULTRA-TURRAX® homogenizer (IKA®, Germany) (10,000 rpm; 1 min) and the volume of produced foam was measured in a graduated 50 ml Falcon tube. FC was calculated as the volume of foam using the formula: FC(%) = (Vf-V0)/V0 x 100 where; V0 is the initial volume of protein solution before homogenization and Vf is the volume of foam produced after homogenization. The foaming stability (FS) was calculated using the same formula, with Vf measured after 15, 30 and 60 min. Emulsifying activity and emulsifying stability The emulsifying activity (EA) of of the blood water permeates and retentate samples were determined using a modified method of Garcia-Vaquero et al. (2017). Each sample was suspended in deionized water to make 1% concentration (w/v) and the pH was adjusted to 2, 4, 6, 8 and 10 with 0.1 N HCl and 0.1 N NaOH. The solution was homogenized for 30 s at 14,000 rpm using a T 25 digital ULTRA-TURRAX® homogenizer (IKA®, Germany). The emulsion was created by addition of sunflower oil to aqueous phase (oil:sample solution = 3:2) in 50 ml Falcon tubes. The oil was added in two steps: half of the volume was first added, and the mixture was homogenized 30 s at 14000 rpm, after which the rest of the oil was added and homogenization was repeated for 90 s at the same speed. The tubes containing emulsion were then centrifuged at 1100 × g for 5 min and the volume of the emulsion layer was recorded. Emulsifying activity was calculated by the formula: EA (%) = (Ve/Vt) x 100 Being Ve the volume of the emulsion layer after centrifuging and Vt the all volume inside the tube. Emulsion stability (ES) was determined by heating the previously prepared emulsions at 85 °C for 15 min, cooling at room temperature for 10 min and centrifuging again 1100 × g for 5 min. The ES was calculated and expressed as the % of EA after heating and centrifuging centrifuging by the formula: ES (%) = (V emulsion after heating/ V original emulsion ) x 100 ACE-I inhibition assay ACE-I (angiotensin-converting enzyme I) inhibition bioassay of permeate and retentate samples (Mackerel and Blue whiting) was carried out according to the manufacturer’s instructions (ACE Kit—WST, Dojindo Laboratories, Kumamoto, Japan). In brief, 20μL of each sample aqueous solution at a concentration of 1 mg/mL was added to 20μL substrate and 20μL enzyme working solution in triplicate. Captopril was used as a positive control. Samples were incubated at 37◦C for 1 h. A 200μL of indicator working solution was then added to each well, and subsequent incubation at room temperature was carried out for 10 min. Absorbance at 450 nm was read using a FLUOstarOmega microplate reader (BMG LABTECH GmbH, Offenburg, Germany). The percentage of inhibition was calculated using the following equation: % ACE-I inhibition = 100% Initial activity−Inhibitor × 100/100% Initial activity Renin inhibition assay Renin inhibition activity of permeates and retentate fractions was tested in vitro for renin. The bioassay was carried out according to the manufacturer’s instructions (Renin Inhibitor Screening Assay Kit, Cayman chemical, Ann Harbor, MI, USA). In brief, 10 μL of each fraction solution in dimethyl-sulfoxide (DMSO) at a concentration of 1 mg/mL was added to 20 μL substrate and 150 μL of assay buffer in triplicate. Renin was then added to 100% initial activity and inhibitor wells, the wells were shaken for 10 seconds and incubated at 37◦C for 15 min. Fluorescence (excitation at 345 nm and emission at 490 nm) was read using a FLUOstarOmega microplate reader (BMG LABTECH GmbH, Offenburg, Germany). The percentage of inhibition was calculated using the following equation: % Renin inhibition = 100% Initial activity−Inhibitor × 100/100% Initial activity Peptide identification by tandem mass spectrometry The nano-LC-MS/MS analysis was performed using an Eksigent Nano-LC Ultra 1D Plus system (Eksigent of AB Sciex, CA) coupled to the quadrupole-time-of-flight (Q-ToF) TripleTOF® 5600 system from AB Sciex Instruments (Framingham, MA) that is equipped with a nano-electrospray ionization source. Samples were re suspended in 50 μL of 0.1% TFA in 2% ACN. 2 µl of every sample were loaded onto a trap column (Nano-LC Column, 3µ C18-CL, 350 μm x 0.5mm; Eksigent) and desalted with 0.1% TFA at 3µl/min during 5 min. After 5 min of preconcentration, the trap column was automatically switched in-line onto a nano-HPLC capillary column (3µm, 75µm x 12.3 cm, C18) (Nikkyo Technos Co, Ltd. Japan). Mobile phase A contained 0.1% v/v formic acid in water, and solvent B, contained 0.1% v/v FA in 100% acetonitrile. A linear gradient from 5% to 35% of solvent B over 60 min at a flow rate of 0.3 μL/min and running temperature of 30 °C was used for chromatographic separations. The column outlet was directly coupled to a nano-electrospray ion (nESI) source. Operating conditions for the Q/ToF mass spectrometer were positive polarity and data-dependent mode. Sample was ionized applying 2.8 kV to the spray emitter. Survey MS1 scans were acquired from 350–1250 m/z for 250 ms. The quadrupole resolution was set to ‘UNIT’ for MS2 experiments, which were acquired 100–1500 m/z for 50 ms in ‘high sensitivity’ mode. Following switch criteria were used: charge: 1+ to 5+; minimum intensity; 70 counts per second (cps). Up to 25 ions were selected for fragmentation after each survey scan. Dynamic exclusion was set to 15 s. The system sensitivity was controlled with 2 fmol of 6 standard proteins (LC Packings). Data analysis Automated spectral processing, peak list generation, and database search for the identification of the peptides were performed using Mascot Distiller v2.7.1.0 software (Matrix Science, Inc., Boston, MA) (hppt://www.matrixscience.com) using MascotServer v2.6 (Matrix Science, Inc., Boston, MA) (hppt://www.matrixscience.com). The UniProt protein database was used to identify the peptides with a significance threshold p<0.05. Used taxonomy for the identification in database was chordata organisms. The tolerance on the mass measurement was 0.3 Da in MS mode and 100 ppm in MS/MS ions. In silico digestion of identified peptides The identified peptides were digested in silico using BioPep online analysis tools (http://www.uwm.edu.pl/biochemia/index.php/en/biopep), with pepsin (EC 3.4.23.1), trypsin (EC 3.4.21.4) and chymotrypsin A (EC 3.4.21.1) in order to simulate gastric digestion process (Minkiewicz et al., 2008). The results of in silico enzyme hydrolysis was then searched for active fragments in BioPep database to identify potential ACE-I inhibitory peptides that may be released during digestion. RESULTS Yield and proximate composition of blood water fractions The freeze-dried filtration fractions had a wide range of protein content, with Blue whiting 3 KDa permeate (BW 3KDa) containing only 11.1 (± 1.53) % of protein, up to 40.5 (± 0.16) % in Markerel 10 KDa permeate (Mac 10 KDa) sample. Other filtration fractions, Blue whiting 10 KDa permeate (BW 10 KDa), Blue whiting retentate (BW Ret), Mackerel 3 KDa permeate (Mac 3 KDa) and Mackerel retentate (Mac Ret) had protein content between those values (13.3 ± 2.17%, 28.9 ± 0.78%, 21.5 ± 0.84% and 29.9 ± 0.45%, respectively). All permeate fractions had a low lipid content (<1%), while BW Ret and Mac Ret had 1.55 (± 0.20) % and 1.69 (± 0.11) % fat, respectively. All dried fractions had ash content over 50 %, with BW 3 KDa and BW 10 KDa containing over 70 % (73.0 ± 0.98 % and 75.8 ± 2.01 %, respectively) and Mac 3 KDa containing 67.4 ± 1.91 % ash. Bw Ret and Mac Ret retentate fractions and Mac 10 KDa permeate fraction contained similar ash content (50.2 ± 0.31 %, 51.9 ± 0.49 % and 53.0 ± 0.18 %, respectively). All the tested fractions had water activity (Aw) values below 0.3, which indicates proper drying of the samples and ensures good microbial stability. Table 2: Proximate composition and water activity of Blue whiting and Mackerel blood water fractions The total amino acid (TAA) content of Mackerel blood water fractions is presented in Table 3. The Mac Ret and Mac 10 KDa samples had significantly higher total amino acid content (144.7 and 199.9 g/Kg, respectively) than Mac 3KDa fraction (65.9 g/Kg). Most abundant detected amino acids were taurine (25.1 g/Kg, 63.4 g/Kg and 2.84 g/Kg in Mac Ret, Mac 10 KDa and Mac 3 KDa, respectively), asparagine (15.3 g/Kg, 8.38 g/Kg and 0.59 g/Kg in Mac Ret, Mac 10 KDa and Mac 3 KDa, respectively) and glutamic acid (13.3 g/Kg, 12.3 g/Kg and 1.20 g/Kg in Mac Ret, Mac 10 KDa and Mac 3 KDa, respectively). All essential amino acids were detected in samples, except tyrosine and tryptophan (which is degraded by acid hydrolysis during sample preparation), with significant concentration of lysine (8.57 g/Kg, 12.2 g/Kg and 0.91 g/Kg in Mac Ret, Mac 10 KDa and Mac 3 KDa, respectively) in all samples.
Table 3: Total amino acid (TAA) composition of Blue whiting and mackerel 10 and 3 kDa filtrates respectively
Table 4: Total amino acid (TAA) composition (g/Kg) of pelagic bloodwaters recovered using MWCO filtration and drying. The mackeral and blue whiting retentates and the 10 kDa and 3kDa fractions are showed comparable to whey protein isolate TAA content and flax TAA content The fatty acid (FA) profile of Mackerel and Blue whiting retentates and 10 KDa permeate fractions is presented in Table 5. The content and profile of detected fatty acids differ significantly between all samples. The Mac Ret sample had 142 (± 11.3) mg of fatty acids per gram of sample, with principal fatty acids being saturated FAs C4:0 (butyric acid, 115 ± 9.44 mg/g lipid) and C8:0 (caprylic acid, 17.5 ± 1.26 mg/g lipid). Main unsaturated fatty acids in this sample, DHA (C22:6) and palmitoleic acid (C16:1), were both present in concentrations below 1 mg/g lipid (0.74 ± 0.13 and 0.45 ± 0.04 mg/g lipid, respectively). The FAMEs profile of Blue whiting retentate (BW Ret), however, is dominated by unsaturated fatty acids (UFAs), which are present at concentration 220 (± 16.0) mg/g lipid in contrast to low concentration of saturated fatty acids (SFA, 57.9 ± 3.79 mg/g lipid). Most abundant unsaturated fatty acids in the BW Ret sample are DHA (C22:6; 111 ± 8.44 mg/g lipid), oleic acid (C18:1 c; 42.8 ± 2.54 mg/g lipid) and EPA (C20:5 n3; 21.6 ± 1.78 mg/g lipid); while stearic acid (C18:0) and myristic acid (C14:0) are the most abundant SFAs (9.68 ± 0.74 and 4.24 ± 0.35 mg/g lipid, respectively). The analysed permeate fractions (Mac 10 KDa and BW 10 KDa) contained only low concentrations of caprilyc acid (in Bw 10 KDa, at 0.49 ± 0.06 mg/g lipid) or combination of caprilyc and capric acid (in Mac 10 KDa, at 105 ± 4.22 and 55.3 ± 1.67 mg/g lipid, respectively).
Table 5: Fatty acid profiles of Mackerel and Blue whiting retentate and 10 KDa permeate fractions The total fatty acids (TFA) content of all the fractions analysed ranged between 293+/-27.6 and 981 +/-29.4 mg/g. Unsaturated fatty acids (UFAs) contributed between 167.3 +/- 9.45 and 786 +/- 22.6 mg/g of the above total whereas polyunsaturated fatty acids (PUFAs) ranged from 75.71 +/- 6.15 to 479.9 +/- 8.94 mg/g. All the samples analysed had a higher content of unsaturated fatty acids compared to their saturated counterparts. The whole fraction of the sample collected on the 30/01/20 from the processing of salmon and white fish had the highest content of unsaturated fatty acids (786 +/- 22.6 mg/g). Polyunsaturated fatty acids have been shown to have beneficial effects on normal health and chronic diseases, by, for example, regulation of immune, lipid levels, and cardiovascular functions. Among the monounsaturated fatty acids (MUFAs), C18:1 cis-9 (oleic acid) was present in higher quantities in all the samples analysed (0 – 231 +/- 7.5 mg/g). The permeate fraction of the sample collected on 30/01/20 from the processing of salmon and white fish had the highest quantity (231 +/- 7.5 mg/g) of oleic acid. Oleic acid has been shown to reduce the levels of low-density lipoprotein in blood which in turn reduces the risk of heart disease and stroke. Other monounsaturated fatty acids, such as C16:1, C18:1 trans, C20:1, and C22:1 were also identified in lower quantities in the range of 0-116 mg/g. In the category of PUFAs, which, were for all but one sample, less in quantity than their MUFAs counterparts, C18:2 cis-9 (linoleic acid) was the dominating fatty acids with quantities of up to 234 +/- 2.7 mg/g. Linoleic acid is an essential fatty acid that plays an important role in the synthesis of eicosanoids, which are involved in a variety of physiological functions. Other important health-related PUFAs such as omega-3 fatty acids C22:6 (DHA) and C20:5 n3 (EPA) were identified with the levels in the ranges of 1.79 +/- 0.44 to 59.07 +/- 1.5 and 1.6 +/- 0.68 to 34.74 +/- 1.5 mg/g. Highest quantities of both EPA (34.7 mg/g) and DHA (59.1 mg/g), were identified in the whole fraction of the samples collected on the 30/01/20 from the processing of salmon and white fish. From the saturated fatty acids group, all the analysed fish blood water fractions contained a significant amount of C14:0, C16:0, C18:0 and C22:0 fatty acids with C16:0 (palmitic acid) dominating this group with the quantities ranging from 26.6 +/- 0.26 to 133.8 +/- 3.9 mg/g. This observation is in line with other studies showing high amounts of C16:0 in fish oil. Other odd number saturated fatty acids such as C13:0, C15:0, C21:0 and C23:0 were also identified, albeit, in very low quantities. Interestingly, for almost every sample analysed, the permeate fraction had the highest amounts of fatty acids compared to the whole and retentate fractions. This data may suggest that the fatty acids investigated in this study are < 3 kDa in size or are mostly associated with the < 3 kDa proteins in the blood water. Based on the above observation, ultrafiltration may be used to concentrate and alter the fatty acid profile of fish blood waters. Techno-functional properties of blood water fractions Water and oil holding capacities Water holding capacities (WHC) and oil holding capacities (OHC) were determined for all Mackerel and Blue whiting retentate and permeate samples. OHC values (g/g) for sunflower and olive oil are presented in Figure 2. WHC values could not be determined using the applied methodology, since all of the tested samples were lost in the process of draining the water supernatant. The calculated OHC were in the range between around 0.5 g/g in case of Mac 3KDa permeate (0.52±0.02 g/g and 0.47±0.02 g/g for sunflower and olive oil, respectively) to around 1.4 g/g for BW Ret sample (1.41±0.02 g/g and 1.39±0.04 g/g for sunflower and olive oil, respectively). Both 10 KDa permeate samples had similar OHC values (0.82±0.04 g/g and 0.80±0.04 g/g for sunflower and olive oil, respectively for Mac 10 KDa and 0.91±0.05 g/g and 0.89±0.09 g/g for sunflower and olive oil, respectively for BW 10 KDa sample). Emulsifying capacity and emulsifying stability The emulsifying activity (EA) and emulsifying stability (ES) of 1% (w/v) sample solutions (Mackerel and Blue whiting retentates and permeates) at pH range from 2 to 10 are presented in Figure 3. EA values of Blue whiting fractions range from 60.0 (±0.00) % in case of BW 3KDa sample at pH=4 to 66.7 (±2.31) % for BW Ret sample at pH=10 and therefore do not differ significantly across the pH range. On the other hand, the EA values of Mackerel samples are significantly lower than Blue whiting samples (ranging from 0.00±0.00 % in case of Mac Ret sample at pH=2 to 36.0±4.00 % for Mac 3 KDa sample at pH=10). Mackerel fractions also show a dependence on the pH value and have significantly higher EA values at high pH (8 and 10). Most of the tested fractions do not show good ES and complete loss of emulsion layer is noticeable under experimental conditions. All emulsion layers of Blue whiting fractions collapse after heating, except the BW Ret fraction, which maintains a good level of EA (40.0±0.00 to 49.3±2.31 %) at all pH values, except at pH=10 where its EA is zero. Mackerel fractions, however, maintained a level of emulsifying activity after heating that ranged from 1.33 (±2.31) % for Mac Ret sample at pH=8 to 14.7 (±2.31) % in case of Mac 3 KDa fraction at pH=10. All Mackerel fractions did not maintain emulsion at pH=2. Foaming capacity, foaming stability and solubility The foaming capacity (FC) and foaming stability (FS) of the 1% (w/v) Mackerel and Blue whiting sample solutions at pH range from 2 to 10 are presented in Figure 4. The 3 and 10 KDa permeate fractions formed foam only at pH=10, ranging from 3.3 (±5.77) % for BW 10 KDa sample to 8.89 (±3.85) % in the case of Mac 3 KDa fraction. Both BW Ret and Mac Ret samples possessed foaming capacities across the entire tested pH range, with values from 6.67 (±0.00) % for Mac Ret sample at pH=6 to 103 (±5.77) % for BW Ret sample at pH=10. FS of the sample solutions after 30 minutes indicates that none of the 3 KDa and 10 KDa permeate fractions did not retain foaming properties. The retentate fractions on the other hand still had foaming properties, with FC values of Blue whiting samples ranging from 23.3 (±5.77) % at pH=4 to 46.7 (±5.77) % at pH=2 and 6. FC values of Mac Ret samples were significantly lower, between 2.22 (±3.85) % and 11.1 (±3.85) % at pH=10 and 4, respectively. No foaming was retained for Mac Ret sample at pH values at 6 and 8. Solubility (S) of 1 % (w/v) sample solutions at pH ranges between 2 and 10 is presented in Figure 5. As can be seen, Blue whiting samples (3 and 10 KDa permeates and retentate) had significantly lower solubilities compared to Mackerel samples across the pH range, with values between 36.9 (±1.42) % (BW Ret at pH=4) and 63.1 (±0.54) % (BW Ret at pH=8); while Mackerel sample solubility ranged between 63.9 (±2.59) % and 98.6 (±0.69) % (Mac Ret at pH=2 and Mac 3 KDa at pH=10, respectively). Bioactivity testing ACE-I and renin inhibition activity The results of ACE-I inhibition activity of the Blue whiting and Mackerel samples tested at 1 mg/mL (w/v) concentration, with Captopril used as positive control, is presented in Figure 6. The activity of Mackerel fractions is significantly different when compared to the tested Blue whiting samples, with Mac 10 KDa and Mac Ret samples having highest inhibition activity (96.9±0.29 % and 95.4±0.11 %, respectively) and Mac 3KDa sample with 83.9 (±18.9) % inhibition. The activity of Blue whiting samples was 59.4 (±16.5), 33.1 (±0.59) and 28.9 (±16.4) % for BW Ret, BW 10 KDa and BW 3KDa samples, respectively. Renin inhibition activity, tested at 1 mg/mL concentration (w/v) of the samples is presented in Figure 7. The inhibition activity ranged from 10.6 (±16.5) % for BW 3KDa sample to 21.0 (±9.22) % for Mac 3KDa sample. Peptide identification by tandem mass spectrometry MS analysis results of the 10 kDa Mackerel and Blue whiting 10 KDa permeate fractions and in Mackerel retentate are presented in Table 6. A total of 65 peptides were identified in the BW 10 KDa sample, 103 peptides were identified in the Mac 10 KDa permeate and 19 peptides in Mac Ret sample. All the identified peptides were identified as novel when checked against the BIOPEP database of known peptides.
Table 6: Identified peptides in Mackerel and Blue whiting 10 KDa permeate fractions and in Mackerel retentate EXAMPLE 2: Skin and bone by-products from Blue Whiting MATERIALS AND METHODS Raw material Blue whiting by-products were kindly supplied by Bord Iascaigh Mhara (BIM) in the form of 4 kg frozen blocks. The blocks consisted of the skin, meat and bones of Blue Whiting caught in Irish waters in March 2017.500 g was used for experiments. The material was thawed at room temperature and then cut into 1 cm pieces prior to use. Skin and bone pre-treatments Four different pre-treatments were applied to blue-whiting by-products independently. Gelatine extraction and gelatine and gelatine hydrolysate freeze-drying steps remained the same throughout the study. The four standard operating procedures (SOPs) for pre-treatment are presented in Table 7.
Table 7: Pre-treatment procedures used for gelatine extraction from Blue Whiting skin and bones Following the pre-treatment steps, by-product skin and bone material was washed with water until neutral (pH 6-7) and gelatine was extracted overnight using water (3:1 v/w to material) at 45 °C in a MaxQ 8000 laboratory shaker (Thermo Fisher Scientific, MA USA) at 200 rpm speed. Solids were removed by filtration through Whatman No 4 filter paper using a Büchi funnel. Resultant clear gelatine extracts were subsequently freeze-dried (FD80GP, Cuddon Freeze Dry, New Zealand) using the following program : Initial temperature -20 °C; 5 steps; run time 90h; end temperature 0 °C. Dried material was placed in sterile, sealed 250 ml containers and stored at -80 °C until analyses. Characterisation of the physical and chemical properties of extracted Gelatines Proximate analysis The yield of gelatine extracted was calculated after freeze-drying and was expressed as a percentage of the total by-product raw material used. The total protein content of the gelatine samples was determined using the Dumas combustion method using a LECO FP328 Protein analyser (LECO Corp, MI USA), according to the Association of Official Analytical Chemists (AOAC) method 992.15 (14). A conversion factor of 6.25 was used to convert total nitrogen to protein. The ash content of the 4 different gelatine extracts was determined gravimetrically, as previously described (15). Water activity Water activity (a w ) values for all samples were determined using an AquaLab Lite meter (Decagon Devices Inc., Germany). Approximately 0.25 g of finely milled sample was placed in the water activity meter and a w and the temperature was recorded (16). pH value pH values of 1% gelatine solutions (w/v) were determined at room temperature using a pH213 pH-meter (Hanna Instruments, TX USA), and buffers pH 4 and pH 7 (Sigma Aldrich, Ireland) were used for calibration in accordance with the method described by GME (17). Lowest gelling concentration The lowest gelling concentrations (LGC) of the Blue-whiting derived gelatines were determined using the method of Ogunwolu et al. (18), and results were expressed as the concentration (w/v) of gelatine solution which could form a gel at 4 °C. Briefly, 2 ml of a range of concentrations of each gelatine solution (1, 2, 5, 8 and 10%; w/v) was measured in a 15 ml Falcon tube and placed in the laboratory refrigerator set to 4 °C for 2 hours. The concentration at which the solution would stop flowing in the tube was recorded as the LGC. Colour measurement Colour measurements were carried out using a Minolta Lab colorimeter (CR-400/410, Konica, Minolta, Ireland) in accordance with previously described methods (19). White and black standard tiles were used to calibrate the instrument prior to measurements. Readings were reported in the CIE L*, a*, and b* system, as L* (lightness), a* (redness/greenness), and b* (yellowness/blueness). The chroma (C*) values were calculated using the following equation (20): Sodium dodecyl sulphate-polyacrylamide gel electrophoresis (SDS-PAGE) Extracted gelatine samples were prepared for sodium dodecyl sulphate polyacrylamide electrophoresis (SDS-PAGE) analysis according to a previously described method (7). SDS- PAGE was carried out using the discontinuous Tris-tricine buffer system (Sigma Aldrich, Ireland). Briefly, gelatine extracts (1%, w/v) were diluted with sample buffer containing 0.2 M Tris–HCl, pH 6.8 containing 2 % (w/v) SDS, 40 % (v/v) glycerol, 0.04% (w/v) Coomasie Blue G250 and 2 % (v/v) 2-mercaptoethanol at the ratio of 1:1 (v/v) and heated to 95 °C for 5 min. The gels used for electrophoresis were the Bio-Rad Mini-Protean Tris-tricine precast gels (4- 20%). Gelatine samples were run in a Mini-Protean® Tetra Cell (Bio-Rad Laboratories, Watford, United Kingdom) at a constant voltage of 100 V. Gels were then fixated in 40% methanol, 10% acetic acid (v/v, in water) and stained with Biosafe Coomassie G250 Stain. The load volume was 20 μL in all lines. A Bio-Rad Precision Plus Protein™ unstained protein molecular weight standard (Bio-Rad Laboratories, Watford, United Kingdom), MW range (10- 250 KDa) and a LW range standard (4-250 kDa) was used to identify the protein fractions. Band detection and molecular weight calculation was done using GelAnalyzer 2010a software (http://www.gelanalyzer.com). Determination of techno-functional properties Water and oil holding capacities The water holding capacity (WHC) and oil holding capacity (OHC) of extracted gelatines were measured using the modified methods described by Neto et al. (21). In brief, 100 mg of each gelatine sample was mixed with 1 ml of distilled water or oil (olive and sunflower oil) using a vortex mixer (VV3, VWR International Ltd., Ireland) for 30 seconds. The suspension was then centrifuged at 2200 × g for 30 min (Eppendorf MiniSpin, Eppendorf UK Limited, United Kingdom) at 19 °C. The supernatant was then decanted by draining the tubes at 45° angle for 10 min (20 min for oil). Water/oil holding capacity was calculated by dividing the weight of water/oil absorbed by the weight of the protein sample and expressed as grams of water or sunflower oil held by 1 g of protein. Solubility Solubility in water (S) was determined using the modified method of Ogunwolu et al. (18).100 mg of each gelatine sample was dispersed in 10 ml de-ionised water. Using a pH-meter (Mettler Toledo, Barcelona, Spain), the pH of the dispersions was adjusted to 2, 4, 6, 8 and 10 with 0.1 N HCl and 0.1 N NaOH. The mixture was vortexed at room temperature (19-20 °C) for 5 min, and subsequently centrifuged at 7500 × g for 15 min (Lynx 6000, Thermo Fisher Scientific, MA USA). The protein content in the supernatant was determined using the Pierce™ BCA (bicinchoninic acid) Protein Assay Kit (Thermo Fischer Scientific, MA USA). Gelatine solubility at different pH conditions was then calculated using the following equation: S (%) = (protein content in the supernatant/protein content in full dispersion) x 100. Foaming capacity The foaming capacity (FC) of the gelatine samples was determined by the modified method described by Bencini (22). Gelatine was suspended in deionized water to make 1% concentration (w/v) and the pH was adjusted to 2, 4, 6, 8 and 10 with 0.1 N HCl and 0.1 N NaOH. The suspensions were homogenized using a T 25 digital ULTRA-TURRAX® homogenizer (IKA®, Germany) (10,000 rpm; 1 min) and the volume of produced foam was measured in a graduated 50 ml Falcon tube. FC was calculated as the volume of foam using the formula: FC (%) = (V f -V 0 )/V 0 x 100 where; V0 is the initial volume of protein solution before homogenization and Vf is the volume of foam produced after homogenization. The foaming stability (FS) was calculated using the same formula, with Vf measured after 15, 30 and 60 min. Emulsifying activity and emulsifying stability The emulsifying activity (EA) of the protein extracts was determined using a modified method of Garcia-Vaquero et al. (20). Gelatine was suspended in deionized water to make 1% concentration (w/v) and the pH was adjusted to 2, 4, 6, 8 and 10 with 0.1 N HCl and 0.1 N NaOH. The solution was homogenized for 30 s at 14,000 rpm using a T 25 digital ULTRA- TURRAX® homogenizer (IKA®, Germany). The emulsion was created by addition of sunflower oil to aqueous phase (oil:gelatine solution = 3:2) in 50 ml Falcon tubes. The oil was added in two steps: half of the volume was first added, and the mixture was homogenized 30 s at 14000 rpm, after which the rest of the oil was added and homogenization was repeated for 90 s at the same speed. The tubes containing emulsion were then centrifuged at 1100 × g for 5 min and the volume of the emulsion layer was recorded. Emulsifying activity was calculated by the formula: EA (%) = (Ve/Vt) x 100 Where; Ve was the volume of the emulsion layer after centrifuging and Vt was the complete volume inside the tube. Emulsion stability (ES) was determined by heating the previously prepared emulsions at 85 °C for 15 min, cooling at room temperature for 10 min and centrifuging again 1100 × g for 5 min. The ES was calculated and expressed as the % of EA after heating and centrifuging centrifuging by the formula: ES (%) = (V emulsion after heating /V original emulsion ) x 100 Microsoft Excel was used for all calculations and graph construction in this study, except in the case of SDS-Page gel analysis, where the GelAnalyzer 2010a software was used for molecular weight estimation. Purified gelatine of bovine (BOV) and porcine (POR) origin (Sigma Aldrich, Ireland) were used for comparison of properties. Enzyme hydrolysis Based on the previously determined chemical, physical and functional properties, gelatine extracts generated using SOP1 and SOP2 were selected for further hydrolysis using the commercial enzymes alcalase and papain. The hydrolysis procedures were undertaken as follows, using a modified procedure described by Lafarga and Hayes (23): Gelatine samples (2.5 g) were dissolved in deionized water (250 ml) to obtain 1% (w/v) gelatine solutions, which were hydrolysed independently with either alcalase ® (EC number 3.4.21.62, activity ≥5 U/g, Sigma Aldrich, Ireland) and papain (EC number 3.4.22.2, activity ≥3 U/mg, Sigma Aldrich, Ireland). The pH values and temperature of each gelatine solution was set before addition of the enzymes as follows: 60 °C and pH 9.5 for Alcalase, 65 °C and pH 6.5 for papain. Solutions were kept in an incubated laboratory shaker (at optimum temperatures, as specified above) during hydrolysis and agitated at 200 rpm. The alcalase was added in a substrate-to enzyme ratio of 100:1 (w/w) and papain was added in 10:1 (w/w) ratio. After incubation, the solutions were heated at 95 °C for 10 min in a water bath to deactivate the enzymes. The pH of solutions was maintained at the optimum value for each enzyme using 0.1 M or 1 M NaOH. After incubation, the degree of hydrolysis (DH) was calculated using the pH-stat method (24), after 1, 60, 120 and 240 min. The DH was then calculated using the following equation: DH = B × N B × 1/α × 1/M p × 1/h tot × 100%, where B (mL) is the volume of NaOH consumed, NB is the normality of the NaOH used, 1/α is the average degree of dissociation of the a-amino groups related with the pK of the amino groups at particular pH and temperatures, M P (g) is the amount of protein in the reaction mixture, and h tot (meq/g) is the sum of the millimoles of individual amino acids per gram of protein associated with the source of protein used in the experiment. Values for h tot and 1/α were obtained from the study conducted by Adler-Nissen (24). Gelatine hydrolysates were freeze-dried as previously described and dried product was kept in sealed containers at -80 °C until further use. Molecular weight cut off filtration Gelatine hydrolysates (0.5 g) were diluted independently in deionized water (10 ml) to a concentration of 5 % (w/v). The solutions (10 ml) were then filtered through 3kDa membrane filters using the Amicon Ultra-15 Centrifugal Filter Unit (Sigma Aldrich, Ireland) at 4000 g for 60 min to obtain fractions with peptides less than 3 kDa in size. Filtrates and permeates were then freeze-dried and the yield of each peptide fraction (≤ 3 KDa) was calculated after weighing. ACE-I inhibition assay ACE-I inhibition activity of gelatine hydrolysates and 3kDa fractions was determined using a bioassay kit in accordance with the manufacturer's instructions (ACE Kit—WST, Dojindo Laboratories, Kumamoto, Japan). In brief, 20μL of each peptide aqueous solution at a concentration of 1 mg/mL was added to 20μL substrate and 20μL enzyme working solution in triplicate. Captopril was used as a positive control (0.5 mg/mL). Samples were incubated at 37 °C for 1 h. A 200μL of indicator working solution was then added to each well, and subsequent incubation at room temperature was carried out for 10 min. Absorbance at 450 nm was read using a FLUOstarOmega microplate reader (BMG LABTECH GmbH, Offenburg, Germany). The percentage of inhibition was calculated using the following equation: % ACE-I inhibition = 100% Initial activity−Inhibitor × 100/100% Initial activity Amino acid composition The total amino acid content of selected gelatine hydrolysates was determined using the method described by Hill (25). Samples were hydrolysed in 6 M HCl at 110 °C for 23 h. The hydrolysed solutions were diluted with 0.2 M sodium citrate buffer (pH 2.2) to give approximately 250 nmol of each amino acid residue. The sample was then diluted 1:1 with the internal standard, norleucine, to give a final concentration of 125 nmol/mL. Amino acids were quantified using a Jeol JLC-500/V amino acid analyser (Jeol Ltd., Garden city, Herts, UK) fitted with a Jeol Na + high-performance cation exchange column. MS analysis Gelatine papain hydrolysates generated from gelatines isolated with SOP1 and SOP2 were selected for MS analysis based on results from techno-functional and bioactivity assays. Samples were cleaned prior to MS analysis using the TiO2 clean-up kit (Pierce, USA). Samples were re-suspended in 50 uL of 0.1% TFA in 2% ACN.5 µl of every sample was loaded onto a trap column (NanoLC Column, 3µ C18-CL, 350 mm x 0.5 mm; Eksigent) and desalted with 0.1% TFA at 3 µl/min during 5 min. The peptides were then loaded onto an analytical column (LC Column, 3 µ C18-CL, 75 umx12cm, Nikkyo) equilibrated in 5% acetonitrile 0.1% FA (formic acid). Elution was carried out with a linear gradient of 5 to 35% B in A for 45 min. (A: 0.1% FA; B: ACN, 0.1% FA) at a flow rate of 300 nl/min. Peptides were analysed in a mass spectrometer nanoESI qQTOF (5600 TripleTOF, ABSCIEX). Sample was ionized applying 2.8 kV to the spray emitter. Analysis was carried out in a data-dependent mode. Survey MS1 scans were acquired from 350–1250 m/z for 250 ms. The quadrupole resolution was set to ‘UNIT’ for MS2 experiments, which were acquired 100–1500 m/z for 50 ms in ‘high sensitivity’ mode. Following switch criteria were used: charge: 1+ to 5+; minimum intensity; 70 counts per second (cps). Up to 25 ions were selected for fragmentation after each survey scan. Dynamic exclusion was set to 15 s. Data analysis procedure ProteinPilot (version 5.0) software from Sciex was used in the data analysis. ProteinPilot default parameters were used to generate peak list directly from 5600 TripleTof wiff files. The Paragon algorithm (26) of ProteinPilot v 5.0 was used to search the NCBI_collagen (162534 searched proteins) database with the following parameters: no enzyme specificity, no taxonomy restriction, and the search effort set to through. The protein grouping was done by Pro group algorithm. RESULTS Proximate analysis The choice of pre-treatment procedure had a significant impact on the yield and proximate composition of the extracted gelatines, as can be seen in Table 8. The yield of dry gelatine recovered was 4.55±0.53 % for SOP1, 4.73±0.41 % for SOP2, 2.22±0.51 % in the case of SOP3, while SOP4 resulted in a yield of 5.02 ±0.89 % gelatine. Although yields are low relative to previous work [(27), (3), (28)], reports on gelatine extraction yields vary greatly throughout available literature [(29), (27), (30), (31)]. The crude protein content of the samples was 86.4±2.49 % for SOP1, 85.6±2.41 in SOP2, 67.6±0.93 in SOP3 and 67.4±5.03 % in SOP4 gelatine sample, while it was 91.7±0.27 % and 94.8±0.29 % in the case of control bovine and porcine gelatines, respectively. The SOP1 and SOP2 samples had similar ash content (5.06±0.15 and 5.95±0.19 %, respectively), while SOP3 sample had an unusually high (23.3±2.86 %) content of ash, and SOP4 sample contained 11.6±0.09 % ash. These determined values were significantly higher than in bovine and porcine control samples, which both contained less than 1% ash (0.68±0.12 and 0.24±0.10 %, respectively). Table 8: physical properties and chemical composition of the gelatine samples Water activity, pH value and LGC The pH values of 1 % (v/w) aqueous gelatine solutions are shown in Table 8. The values for SOP1 and SOP2 samples (pH 7.05±0.02 and pH 6.59±0.02, respectively) were similar to the pH values of the porcine control sample (7.57±0.01); while pH of SOP3 and SOP4 gelatines (4.61±0.02 and 5.03±0.02, respectively) was closer to value determined for bovine gelatine (5.77±0.01). The aw values of the examined samples were 0.26±0.01, 0.44±0.00, 0.52±0.01 and 0.39±0.01 for SOP1, SOP2, SOP3 and SOP4 extracted gelatines after drying, respectively. Bovine and porcine gelatines had comparable water activity (0.42±0.01 and 0.36±0.01, respectively). The lowest gelling concentration (LGC) values of the samples (Table 8) show that SOP1, SOP2 and SOP4 solutions were able to form gels at 4 °C at 2% concentration (w/v), while SOP3 gelatine did not show gelling up until 8% concentration. Both control mammalian gelatines formed gels at 1 % concentrations. Colour measurement The colour parameters of the examined gelatines are presented in Table 9. It can be seen that values of L (lightness) was 95.3±0.73 in the case of SOP1 gelatine, 95.3±0.73 for SOP2, 82.7±3.14 for SOP3 and 94.4±1.93 for SOP4 sample. The b parameter (yellowness/blueness) showed a wide range of determined values, between 2.58±0.85 and 29.5±5.69 (SOP4 and SOP3 samples, respectively); similarly to calculated C value (chroma) of the samples, which was in the range between 2.62 (SOP4) and 29.62 (SOP3). The a parameter (greenness/redness) of all measured samples had negative value, indicating a slight colour shift toward greenness.
Table 9: colour parameters of the gelatine samples Sodium dodecyl sulphate-polyacrylamide gel electrophoresis (SDS-PAGE) The distribution of molecular weights (MW) in the gelatine samples is presented in Figure 8. After identification of bands and calculations of MW using the GelAnalyzer2010a software, the following bands were identified in the examined samples: SOP1: 392 (γ-chain), 232 (β-chain), 134 (α1-chain), 112 (α2-chain), 70, 28, 26, 25 SOP2: 348 (γ-chain), 215 (β-chain), 117 (α2-chain) SOP3: 215 (β-chain), 117 (α2-chain), 74, 54, 36, 31, 28, 26 SOP4: 377 (γ-chain), 215 (β-chain), 114 (α2-chain) BOV: 433 (γ-chain), 232 (β-chain), 137 (α1-chain), 39, 25 POR: 223 (β-chain), 137 (α1-chain), 53, 33, 26, 25 Water and oil holding capacity The water holding (WHC) and oil holding capacity (OHC) of the fish gelatine samples are presented in Figure 9. WHC values for the tested fish gelatines were 3.10±0.04 g/g for gelatine extracted using SOP1, 2.48±0.06 g/g for gelatine extracted using SOP2, 1.48±0.03 g/g for gelatine extracted using SOP3 and 1.79±0.02 g/g for SOP4 gelatine. The control bovine and porcine gelatines had significantly higher WHC values (7.78±0.09 and 8.75±0.17 g/g, respectively). However, OHC values for both sunflower and olive oil were significantly higher for SOP1 (8.08±0.13 g/g and 6.49±0.32 g/g for sunflower and olive oil, respectively) SOP2 (4.86±0.07 g/g and 4.72±0.19 g/g for sunflower and olive oil, respectively) and SOP4 gelatine (5.69±0.05 g/g and 5.38±0.11 g/g for sunflower and olive oil, respectively) samples than values determined for bovine (0.36±0.02 g/g and 0.34±0.03 g/g for sunflower and olive oil, respectively)and porcine (0.39±0.01 g/g and 0.28±0.01 g/g for sunflower and olive oil, respectively) gelatines. OHC values for SOP3 gelatine (0.34±0.02 g/g and 1.12±0.09 g/g for sunflower and olive oil, respectively) were similar to values determined for control gelatines, and significantly lower than the rest of fish gelatine samples. Solubility, foaming capacity and foaming stability Solubility (S) of 1 % (w/v) gelatine solutions at pH ranges between 2 and 10 is presented in Figure 10. The fish gelatines displayed solubility ranging from 76.4±5.63 % (SOP3 sample at pH 10) to 99.6±0.52 % (SOP2 sample at pH 2). The solubility of control gelatine samples was determined to range from 68.7±5.93 % (porcine gelatine sample at pH 8) to 86.0±3.57 % (bovine gelatine sample at pH 4). The foaming capacity (FC) and foaming stability (FS) of the 1% (w/v) gelatine sample solutions at different pH values (2, 4, 6, 8 and 10) are presented in Figure 11. FC values were in the range between 13.4±2.83 % (SOP3 at pH 8) and 75.6±7.70 % (SOP4 at pH 2) in the case of fish gelatine samples. After 60 minutes, the ability to maintain foam decreased significantly and several samples had no foam layer (SOP2 at pH 2, 4 and 6; SOP3 at pH 2, 4, 6 and 8 an SOP4 at pH6), as can be seen from FS values in Figure 10. The control bovine and porcine gelatine samples did not completely lose the FC at any of the tested pH levels, although the determined FS values show a significant decrease foaming activity in general. Emulsifying activity and emulsifying stability The emulsifying activity (EA) and emulsifying stability (ES) of 1% (w/v) fish gelatine solutions at pH range from 2 to 10 are presented in Figure 11. EA values of fish gelatine samples were in the range between 53.3±2.31 % (SOP3 sample at pH 4) and 72.00±0.00 % (SOP2 sample at pH 2), while the control samples showed a wider range of determined EA values from 12.00±0.00 % (bovine gelatine sample at pH 10) to 81.3±2.31 % (porcine gelatine sample at pH 2). ES values showed a slight decrease in emulsifying properties, ranging from 30.7±2.31 % to 61.3±2.31 % (SOP3 at pH 6 and SOP1 sample at pH 2, respectively) and between 8.00±0.00 % and 66.7±2.31 % in the case of control gelatine samples (porcine sample at pH4 and porcine sample at pH 2, respectively). Enzyme hydrolysis The degree of hydrolysis (DH) of SOP1 and SOP2 gelatine sample solutions is presented in Figure 12. After 4 h of hydrolysis, when alcalase was used, the DH reached 1.87±0.02 % and 2.54±0.12 % (SOP1 and SOP2 samples, respectively) and with papain these values were 20.35±0.01 % and 19.38±0.97 % (SOP1 and SOP2 samples, respectively). Since papain in this study was used in higher ratio to sample (1:10, w/w) than alcalase (1:100, w/w) the graph of papain DH shows that, under the applied conditions, the hydrolysis was approaching a plateau at DH values close to 20%. After molecular weight cut-off (MWCO), using 3 kDa membranes the SOP1 and SOP2 papain hydrolysates had yields of 42.1±0.54 % and 43.2±1.67 %, respectively, while the alcalase hydrolysates of gelatines from SOP1 and SOP2 yielded 3kDa hydrolysate fractions of 10.9±0.89 % and 9.3±0.61 % respectively. Amino acid composition The total amino acid composition of SOP1 and SOP2 gelatine samples and their papain hydrolysates are presented in Table 10. The main amino acids detected included glycine (190.4 to 210.6 g/Kg), glutamic acid (78.7 to 84.6 g/Kg), alanine (72.7 to 80.5 g/Kg) and proline (76.6 to 86.7 g/Kg). The sum of the total amino acids ranged from 749.9 g/Kg (SOP2 papain hydrolysate) to 800.9 g/Kg (SOP1 papain hydrolysate), which accounted for 74.9 % and 80.1 % of the total sample weights, respectively. The results of ACE-I inhibition assay are presented in Figure 13. The alcalase hydrolysates had ACE-I inhibition values of 26.8±4.47% and 25.1±2.72% for SOP1 and SOP2 gelatine hydrolysates, respectively when compared to Captopril (99.48% at 0.5 mg/ml). The ≤3 KDa peptide fractions of the corresponding alcalase hydrolysates had 84.2±3.38% and 87.1±1.83% ACE-I inhibition when assayed at 1 mg/ml concentrations. Gelatine hydrolysates generated using papain resulted in ACE-I inhibition values of 73.1±2.72% and 71.1±0.00% for SOP1 and SOP2 gelatine hydrolysates, respectively when compared to Captopril (99.48% at 0.5 mg/ml). The ≤3 KDa peptide fractions of the corresponding hydrolysates had 80.5±1.83% and 84.5±0.00% ACE-I inhibition when assayed at 1 mg/ml concentrations. MS analysis MS analysis of the 3 kDa fractions generated from gelatines isolated using SOP1 and SOP2 and hydrolysed with papain are presented in Table 11. A total of 81 peptides were identified in the papain gelatine hydrolysate made using gelatine isolated with SOP1, while 90 peptides were identified in the hydrolysate generated using papain and gelatine isolated with SOP2. All the identified peptides were identified as novel when checked against the BIOPEP database of known peptides.
Table 11: Identified peptides in papain hydrolysates ≤ 3 KDa peptide fractions
Table 12: amino acids identified in the retentate and 10-kDa fractions recovered using MWCO of gelatine hydrolysates generated using papain and alcalase. Gelatine is a denatured protein derived by partial hydrolysis of collagen. Discussion Yields and proximate composition of gelatines It is known that numerous factors, including fish species, quality of by-products, the pre- treatment steps and the extraction time and temperature can influence the yield of gelatine produced. In this study, the by-product consisted of a mixture of fish skin, bones and muscle left after industrial processing of blue whiting into surimi products. As can be seen from Table 8, gelatines extracted using SOP1, SOP2 and SOP4 procedures produced similar yields of gelatine (around 5 %), while the yield of gelatine obtained using SOP3 was significantly lower. SOP1 and SOP2 gelatine samples also had high protein and low ash contents compared to gelatines generated using SOP3 and SOP4. Notably, the LGC of SOP1, SOP2 and SOP4 gelatines was approximately 2 % (w/v), while gelatine generated using SOP3 had gelling properties only at significantly higher (8 %, w/v) concentrations. Solutions of SOP1 and SOP2 gelatines had pH values closer to neutral, while gelatines generated using SOP3 and SOP4 had pH values in the range of X-X. The water activities of the samples after freeze-drying were comparable to the aw of bovine and porcine gelatines. This indicates that the gelatines are safe for use. Most pathogenic bacteria require a w value of above 0.91, and a product can be considered microbiologically stable if its Aw is under 0.6 (32). A decrease in L (lightness) parameter indicates a general darker colour, and it can be seen that SOP1, SOP2 and SOP4 samples compare favourably to the control gelatines (Table 9). The notable exception is the enzymatically pre-treated SOP3 gelatine, which shows the lowest L value of all samples, as well as highest value of b (yellowness/blueness) parameter corresponding to its strong yellow coloration. C (Chroma) value is a tool for expressing the colour intensity, and from the calculated C values it can be clearly seen that SOP3 gelatine had the most intense colouring. The SDS-PAGE (Figure 8) results show that SOP1, SOP2 and SOP4 gelatine samples have similar protein patterns and consist of γ-, β- and α- protein chains, with other minor bands that indicate varying levels of sample hydrolysis. In the SOP3 gelatine sample, however, absence of the heavy γ- chain and strong presence of lower molecular weight bands indicate an increased level of protein hydrolysis. Previously, Jellouli et al. (33) reported a yield of 5.67% gelatine from fish skins of the grey triggerfish (Balistes capriscus) when pre-treatment with 0.2 mol/L of NaOH and 0.05 mol/L of acetic acid was used, while others including Balti et al. (34), reported a lower gelatine yield (2.21%) when protease enzyme was used as a pre-treatment in the case of cuttlefish (Sepia officinalis) skin gelatine. According to the Gelatine Handbook (35) specifications, edible gelatine should normally contain between 0.3 – 2% ash, depending on the production process, and ash content of the samples in this study was higher than these limits. It is known that the colour of fish sourced gelatine may vary widely, depending on the fish species, raw material, pre-treatment and extraction process, although it generally does not affect its functional properties. Recently, Kittiphattanabawon et al. (30) have investigated the influence of extraction conditions on the properties of gelatine obtained from Clown featherback (Chitala ornata). Their results showed a decrease in MW bands (γ-, β- and α1-chains) intensity with the increase of extraction time and temperature. In our study, the extraction temperature and time were kept constant in all SOPs, so it can be concluded that pre-treatment conditions also show a pronounced effect on the protein distribution in extracted fish gelatines. Limitations concerning the applications of fish gelatine are mainly due to lower gel strengths and stability and lower gelling and melting temperatures in comparison to mammalian-sourced gelatines (1). These differences are especially prominent in the case of gelatines extracted from cold- water fish species, which are known to contain smaller number of imino acids (proline and hydroxyproline) and a larger quantity of higher non-polar amino acids (36). The properties of gelatines produced during our experiments are in accordance with literature reports comparing cold-water fish gelatines to warm-water species and mammalian sources [(1), (37)]. Therefore, non-modified gelatines obtained from cold-water fish species, such as blue whiting, may not be successfully used in applications where gelling at room temperature is required (e.g. production of jelly desserts). Techno-functional properties of gelatines WHC refers to the ability of protein to absorb water and retain it against a gravitational force within the protein matrix (38). The WHC values of the SOP1, SOP2, SOP3 and SOP4 gelatines (Figure 9) were significantly lower than the controls bovine and porcine-derived gelatines. Ability to retain water is largely dependent on the hydrophilicity of the gelatine, with gelatines of mammalian origin being generally richer in hydrophilic amino acids, mainly proline and hydroxyproline, compared to fish sourced gelatines. Also, the low WHC values observed may be partially explained by high solubility of fish gelatine in water and the inability of the produced samples to form gel at room temperature. SOP1 gelatine had the highest OHC values for both sunflower and olive oil. SOP2 and SOP4 samples had comparable OHC, while SOP3 sample had the lowest values for both OHC and WHC of all the produced samples. Fat binding capacity depends on the degree of exposure of the hydrophobic residues inside gelatine, and therefore gelatines obtained from cold water fish species, richer in hydrophobic amino acid residues, may show a better OHC and lower WHC compared to mammalian gelatines. Results in this study show significant differences in WHC and OHC values, implying that the products obtained from blue whiting belong to the cold water fish gelatine type, and could be potentially be utilized as food emulsifiers. The solubility of all gelatine samples (Figure 10) in water was high for all samples, with SOP1 and SOP2 samples being the most soluble (solubility over 80 %) at all tested pH levels. SOP3 and SOP4 samples also had high solubility, which was comparable to bovine and porcine gelatines. The FC (Figure 10) of all investigated gelatine solutions was highest at pH=2 and was comparable to control gelatine values. At all other tested pH values, the FC of fish gelatine samples (SOP1, SOP2, SOP3 and SOP4) and control gelatines were comparable and were less than 50%. SOP3 derived gelatine had a significantly lower FC than the other samples. This is in accordance with literature findings which indicate that foam stability of protein solutions is usually positively correlated with the molecular weight of peptides. FS values after 60 min in Figure 10 show that the foam of fish gelatine samples had lower stability in comparison to control samples. The hydrophobic areas in the gelatine peptide chain influence its amphoteric characteristics, enabling it to be used as an emulsifying agent in various applications (cooking, manufacture of desserts, oil-in-water emulsions such as low-fat margarine, salad dressings, milk cream and others). The 1% (w/v) fish gelatine solutions in our experiment have produced significant emulsifying activity (EA) and emulsifying stability (ES) with sunflower oil (Figure 11) over the tested ranges of pH values (2-10) compared to the controls. EA of all gelatine samples was highest at pH=2. Bovine and porcine gelatines, had significantly lower EA and ES at pH=10 and pH=4, respectively. On the basis of the results obtained in this study, it can be concluded that pre-treatment has a considerable influence on the properties of gelatine extracted from Blue whiting by-product consisting of skin, bones and meat. The combination of alkaline, diluted mineral acid and diluted acetic acid pre-treatment in the case of SOP1 and SOP2 samples has proven to yield gelatine with best physical and chemical properties and most optimal techno-functional characteristics. Using mild organic acid (citric acid) for the tested period of time has produced a highest yield of gelatine with best colour characteristics, albeit with high mineral content and less optimal techno-functional characteristics. In the case of SOP3 pre-treatment, which consisted of enzymatic hydrolysis (using alcalase) and subsequent treatment with mineral acid, the gelatine produced had notably inferior physical and chemical characteristics, lower yield and significantly impaired techno-functional properties. This indicates an excessive level of collagen hydrolysis if alcalase is used, which was further substantiated by the results of SDS-PAGE protein analysis. Enzyme hydrolysis Enzymatic hydrolysis of food by-products is an interesting strategy for by-product utilisation. The interest of numerous researchers is particularly focused on hydrolysis of marine processing by-products, since it has been shown that many of the hydrolysis products possess various biological activities, such as antioxidant, antihypertensive, antibacterial and anti- obesity effects. Based on the overall properties of the gelatines developed in this study, gelatines generated using SOP1 and SOP2 were chosen for further hydrolysis using alcalase, and papain enzymes. Determination of the degree of hydrolysis (DH) is an important step in characterization of protein hydrolysates for use in functional food products. Also, it is known that DH has an important role in ACE-I inhibitory activity, with higher DH values principally indicating better potential bioactivity. Although optimal conditions for the enzymatic hydrolysis were applied, the attained degree of hydrolysis differed significantly between the samples. Hydrolysis of gelatine using resulted in a DH values of 20The DH of gelatine using alcalase was 2.54±0.12% for SOP2 derived gelatine. Bioactivity of papain hydrolysates The in vitro ACE-I inhibitory activities of the alcalase and papain hydrolysates were calculated at a concentration of 1 mg/ml and Captopril® (0.5 mg/ml) was used as positive control. The increase in bioactivity of the low molecular weight fraction is in agreement with previously reported findings implying that lower molecular weight peptides are principally responsible for ACE-I inhibition in protein hydrolysates. When alcalase was used for hydrolysis of gelatines, the differences between the ACE-I inhibitory activity of whole hydrolysates and ≤3 KDa peptide fractions were significant. This was however not the case when papain was used for hydrolysis, where whole hydrolysates had activity comparable to the purified ≤3 KDa peptide fractions. This can be explained by more complete protein hydrolysis when papain was used, which is shown by higher calculated DH values. MS analysis of peptides The ≤3 KDa peptide fractions of the papain hydrolysates were determined to have the highest ACE-I inhibitory activity and were therefore selected for MS analysis in order to determine their peptide composition. All of the determined peptides (81 in SOP1 sample and 90 in SOP2 sample) were found to be unique when compared to peptides in the BIOPEP peptide database. The amino acid composition of the hydrolysates was similar to the intact gelatine samples, and the results show that most abundant amino acids within peptide sequences were glycine (190.4 to 210.6 g/Kg), glutamic acid (78.7 to 84.6 g/Kg), alanine (72.7 to 80.5 g/Kg) and proline (76.6 to 86.7 g/Kg). It has been suggested that residues with bulky hydrophobic side-chains (proline, tryptophan, tyrosine and phenylalanine) are the most effective amino acids for inhibition of ACE-I in dipeptides, but also the N-terminal side of peptide inhibitors may benefit from small, as well as hydrophobic side chains such as leucine, valine and isoleucine (45). The peptides that were identified with ≥99.0 % analytical confidence (37 in SOP1 and 39 in SOP2 sample) were checked against FASTA sequences of the corresponding proteins used for confirmation in the NCBI protein database. The structure of most identified peptides (36 in SOP1 sample and 37 in SOP2 sample) was confirmed in this manner, and the corresponding proteins show a strong correlation between amino acid sequence of identified peptides and alpha-chain collagen sequences. The identified peptides were then searched for the potential bioactive fragments using the BIOPEP (46) analysis tools. The search resulted in numerous identified fragments with ACE- I inhibitory activity, such tripeptides GPL, PGL, GPM, DGL and dipeptides PP, PG, GG, AG, and IG in the tested peptide sequences. EXAMPLE 3: Control recipe for dog biscuit 49.5 g wheat flour 1.0 g sodium chloride 7.4 g sucrose 0.8 g sodium hydrogen carbonate 1.8 g sodium phosphate (dibasic) 9.9 g sunflower oil 29.6 g water Test sample 1 Substitute 10g of flour with 10g 3kDa fraction Test sample 2 Substitute 10g of flour with 10g 10kDa fraction Test sample 3 Substitute 10g of flour with 10g retentate fraction Methodology Mix and homogenize ingredients, add water and oil and knead to obtain soft dough. The dough was rested for 15 to 20 minutes, rolled on a plate to approximately 0.5cm thickness and cut. The biscuits were baked at 140°C for 45 minutes in a convection oven. Results Figure 15 illustrates a method for making a biscuit of the invention. A rich brown colour was achieved during baking with bloodwaters but not with blue-whiting derived proteins from skin and bones. The mixture necessitates the use of lower than normal batch water temperatures during baking to achieve a “spring” or rise in the biscuit. The colour of the biscuit was tested: For the gelatine hydrolysate – It can be seen that values of L (lightness) parameter ranged from 82.7 (±3.14) for SOP3 sample to 95.3 (±0.73) in the case of SOP1 sample. The b parameter (yellowness/blueness) showed a wide range of determined values, between 2.58 (±0.85) and 29.5 (±5.69) (SOP4 and SOP3 samples, respectively); similarly to calculated C value (chroma) of the samples, which was in the range between 2.62 (SOP4) and 29.62 (SOP3). A parameter (greenness/redness) of all measured samples had negative value, indicating a slight colour shift toward greenness. EXAMPLE 4: Anti-hypertensive effect in dogs in vivo. The gelatine samples were generated from the raw material using SOP2. 250 g (X 3) of whole, blue-whiting H&G material was minced in a food blender for 30 seconds and subsequently added to 250 ml of distilled, deionised water. The slurry obtained was heated for 10 min at 80 ˚C to inactivate endogeneous enzymes. Hydrolysis was carried out at 140 rpm, 55 ˚C, pH 8 using the enzyme alcalase® which was added to the H&G material at the ratio of 1:100 (w:v). Hydrolysis was carried out for 4 hours. The volume of 0.1 M NaOH used to adjust the pH of the hydrolysate to 6.5 was noted and hydrolysis was terminated by heating at 95 ˚C for 10 min to inactivate the added enzyme. The hydrolysate was cooled to room temperature, the hydrolysate slurry was poured into trays, frozen and then freeze-dried using a Labconco freeze drier (Labconco corporation, USA) and a set programme for 48 h. The freeze-dried hydrolysates were weighed to calculate yield by-product H&G per batch and hydrolysates were subsequently analysed for protein, lipid and other components. Formulation and baking conditions for PAW dog biscuits containing H& G whole alcalase hydrolysate or H&G gelatine papain hydrolyate or mussel whole papain hydrolyate at a concentration of 10 %. Control recipe (for 600g of dough) Flour: 268g Sunflower oil: 50g Sugar: 37g Water: 145g Additional flour (for rolling and kneading): 100g Experiment recipe (for 600g of dough, around 10% added protein): Flour: 243g X blood-water: 25g Sunflower oil: 50g Sugar: 37g Water: 145g Additional flour (for rolling and kneading): 100g Baking procedure: Mix ingredients; knead for 3-5 minutes. Roll the dough using automatic sheeter (to approx 3.5 mm thickness) and cut out biscuits using cutter. Put on non-stick baking tray and bake in pre- heated oven at 150 °C for 40 min. Water loss factor: approximately = 0.76 Cookies without test ingredient marked as “Control” and cookies with test ingredients named M Cookies (Mussel papain hydrolysate cookies) and H&G cookies (Blue whiting H&G hydrolysate cookies) were used in in vivo dog studies. The study was performed at an approved pet kennel in the Netherland (Kennel De Morgenstond). All tests carried out were non-invasive and did not harm the animals or the wellbeing of the animal. The study was executed with ten senior dogs (8-13 years old) over three weeks (21 days). A “matched pair design” format was used in this study. Experimental protocols with the animals is attached in Appendix A.1 (2+5, where 2 days adjustment on new feed/snack, 5 days recording period). For the first week, dogs are fed with the control cookies. After the first 7 days, dogs were then on a break for 2 days and were then in the new test for 5 days. During the course of the whole study, dogs were given 500g of Pedigree kibbles (The proximate analysis of the kibble feed is shown in table 4.1). During the control period, in addition to food, each dog was offered 2 control biscuits per day. The same procedure was repeated for the test diets. Results Measurement of blood pressure of the dogs showed a significant decrease in BP when the H&G (headed and gutted) gelatine hydrolysate cookie was given to dogs compared to the control (Figure 22). Alcalase® was used as the enzyme to obtain the hydrolysate. The dogs were tested and fed the cookie over 5 days. References 1. Sinthusamran, S.; Benjakul, S.; Kishimura, H., Characteristics and gel properties of gelatin from skin of seabass (Lates calcarifer) as influenced by extraction conditions. Food Chemistry 2014, 152, 276-284. 2. Haddar, A.; Bougatef, A.; Balti, R.; Souissi, N.; Koched, W.; Nasri, M., Physicochemical and functional properties of gelatin from tuna (Thunnus thynnus) head bones. Journal of Food & Nutrition Research 2011, 50. 3. Lassoued, I.; Jridi, M.; Nasri, R.; Dammak, A.; Hajji, M.; Nasri, M.; Barkia, A., Characteristics and functional properties of gelatin from thornback ray skin obtained by pepsin- aided process in comparison with commercial halal bovine gelatin. Food Hydrocolloids 2014, 41, 309-318. 4. Uhlmann, S. S., The European Landing Obligation: Reducing Discards in Complex, Multi-Species and Multi-Jurisdictional Fisheries. Springer: 2019. 5. Halim, N. R. A.; Yusof, H. M.; Sarbon, N. M., Functional and bioactive properties of fish protein hydolysates and peptides: a comprehensive review. Trends in Food Science & Technology 2016, 51, 24-33. 6. Hayes, M.; Mora, L.; Hussey, K.; Aluko, R. E., Boarfish protein recovery using the pH- shift process and generation of protein hydrolysates with ACE-I and antihypertensive bioactivities in spontaneously hypertensive rats. Innovative Food Science & Emerging Technologies 2016, 37, 253-260. 7. García-Moreno, P. J.; Espejo-Carpio, F. J.; Guadix, A.; Guadix, E. M., Production and identification of angiotensin I-converting enzyme (ACE) inhibitory peptides from Mediterranean fish discards. Journal of Functional Foods 2015, 18, 95-105. 8. Elavarasan, K.; Shamasundar, B. A.; Badii, F.; Howell, N., Angiotensin I-converting enzyme (ACE) inhibitory activity and structural properties of oven-and freeze-dried protein hydrolysate from fresh water fish (Cirrhinus mrigala). Food chemistry 2016, 206, 210-216. 9. López-Barrios, L.; Gutiérrez-Uribe, J. A.; Serna-Saldívar, S. O., Bioactive peptides and hydrolysates from pulses and their potential use as functional ingredients. Journal of food science 2014, 79, R273-R283. 10. Koli, J. M.; Basu, S.; Nayak, B. B.; Patange, S. B.; Pagarkar, A. U.; Gudipati, V., Functional characteristics of gelatin extracted from skin and bone of Tiger-toothed croaker (Otolithes ruber) and Pink perch (Nemipterus japonicus). Food and bioproducts processing 2012, 90, 555-562. 11. Tabarestani, H. S.; Maghsoudlou, Y.; Motamedzadegan, A.; Mahoonak, A. R. S., Optimization of physico-chemical properties of gelatin extracted from fish skin of rainbow trout (Onchorhynchusmykiss). Bioresource Technology 2010, 101, 6207-6214. 12. Khiari, Z.; Rico, D.; Martin-Diana, A. B.; Barry-Ryan, C., Comparison between gelatines extracted from mackerel and blue whiting bones after different pre-treatments. Food chemistry 2013, 139, 347-354. 13. Niu, L.; Zhou, X.; Yuan, C.; Bai, Y.; Lai, K.; Yang, F.; Huang, Y., Characterization of tilapia (Oreochromis niloticus) skin gelatin extracted with alkaline and different acid pretreatments. Food Hydrocolloids 2013, 33, 336-341. 14. Horwitz, W.; Chichilo, P.; Reynolds, H., Official methods of analysis of the Association of Official Analytical Chemists. Official methods of analysis of the Association of Official Analytical Chemists.1970. 15. Kolar, K., Gravimetric determination of moisture and ash in meat and meat products: NMKL interlaboratory study. Journal of AOAC International (USA) 1992. 16. Barbosa-Cánovas, G. V.; Fontana Jr, A. J.; Schmidt, S. J.; Labuza, T. P., Water activity in foods: fundamentals and applications. John Wiley & Sons: 2008; Vol.13. 17. Safety. https://www.gelatine.org/gelatine/safety.html files/153/safety.html 18. Ogunwolu, S. O.; Henshaw, F. O.; Mock, H.-P.; Santros, A.; Awonorin, S. O., Functional properties of protein concentrates and isolates produced from cashew (Anacardium occidentale L.) nut. Food chemistry 2009, 115, 852-858. 19. Musso, Y. S.; Salgado, P. R.; Mauri, A. N., Smart edible films based on gelatin and curcumin. Food hydrocolloids 2017, 66, 8-15. 20. Garcia-Vaquero, M.; Lopez-Alonso, M.; Hayes, M., Assessment of the functional properties of protein extracted from the brown seaweed Himanthalia elongata (Linnaeus) SF Gray. Food Research International 2017, 99, 971-978. 21. Neto, V. Q.; Narain, N.; Silva, J. B.; Bora, P. S., Functional properties of raw and heat processed cashew nut (Anacardium occidentale, L.) kernel protein isolates. Food/Nahrung 2001, 45, 258-262. 22. Bencini, M. C., Functional properties of drum-dried chickpea (Cicer arietinum L.) flours. Journal of Food Science 1986, 51, 1518-1521. 23. Lafarga, T.; Hayes, M., Effect of pre-treatment on the generation of dipeptidyl peptidase-IV-and prolyl endopeptidase-inhibitory hydrolysates from bovine lung. Irish journal of agricultural and food research 2017, 56, 12-24. 24. Adler-Nissen, J., Enzymatic Hydrolysis of Food Protein. Elsevier Applied Science Publishers LTD, London, UK: 1986; p 451. 25. Hill, R. L., Hydrolysis of proteins. In Advances in protein chemistry, Elsevier: 1965; Vol.20, pp 37-107. 26. Shilov, I. V.; Seymour, S. L.; Patel, A. A.; Loboda, A.; Tang, W. H.; Keating, S. P.; Hunter, C. L.; Nuwaysir, L. M.; Schaeffer, D. A., The Paragon Algorithm, a next generation search engine that uses sequence temperature values and feature probabilities to identify peptides from tandem mass spectra. Molecular & cellular proteomics : MCP 2007, 6, 1638- 55. 27. Kaewruang, P.; Benjakul, S.; Prodpran, T.; Nalinanon, S., Physicochemical and functional properties of gelatin from the skin of unicorn leatherjacket (Aluterus monoceros) as affected by extraction conditions. Food Bioscience 2013, 2, 1-9. 28. da Trindade Alfaro, A.; Balbinot, E.; Weber, C. I.; Tonial, I. B.; Machado-Lunkes, A., Fish gelatin: Characteristics, functional properties, applications and future potentials. Food Engineering Reviews 2015, 7, 33-44. 29. Jakhar, J. K.; Reddy, A. D.; Maharia, S.; Devi, H. M.; Reddy, G. V. S.; Venkateshwarlu, G., Characterizationof fish gelatin from Blackspotted Croaker (Protonibea diacanthus). Archives of Applied Science Research 2012, 4, 1353-1358. 30. Kittiphattanabawon, P.; Benjakul, S.; Sinthusamran, S.; Kishimura, H., Gelatin from clown featherback skin: Extraction conditions. LWT-Food Science and Technology 2016, 66, 186-192. 31. Hema, G. S.; Joshy, C. G.; Shyni, K.; Chatterjee, N. S.; Ninan, G.; Mathew, S., Optimization of process parameters for the production of collagen peptides from fish skin (Epinephelus malabaricus) using response surface methodology and its characterization. J Food Sci Technol 2017, 54, 488-496. 32. Abbas, K. A.; Saleh, A. M.; Mohamed, A.; Lasekan, O., The relationship between water activity and fish spoilage during cold storage: A review. J. Food Agric. Environ 2009, 7, 86- 90. 33. Jellouli, K.; Balti, R.; Bougatef, A.; Hmidet, N.; Barkia, A.; Nasri, M., Chemical composition and characteristics of skin gelatin from grey triggerfish (Balistes capriscus). LWT- Food Science and Technology 2011, 44, 1965-1970. 34. Balti, R.; Jridi, M.; Sila, A.; Souissi, N.; Nedjar-Arroume, N.; Guillochon, D.; Nasri, M., Extraction and functional properties of gelatin from the skin of cuttlefish (Sepia officinalis) using smooth hound crude acid protease-aided process. Food Hydrocolloids 2011, 25, 943- 950. 35. Gmia, G. H., Gelatin Manufacturers Institute of America. New York 2012. 36. Kittiphattanabawon, P.; Benjakul, S.; Visessanguan, W.; Shahidi, F., Comparative study on characteristics of gelatin from the skins of brownbanded bamboo shark and blacktip shark as affected by extraction conditions. Food Hydrocolloids 2010, 24, 164-171. 37. Araghi, M.; Moslehi, Z.; Mohammadi Nafchi, A.; Mostahsan, A.; Salamat, N.; Daraei Garmakhany, A., Cold water fish gelatin modification by a natural phenolic cross-linker (ferulic acid and caffeic acid). Food science & nutrition 2015, 3, 370-375. 38. Rawdkuen, S.; Thitipramote, N.; Benjakul, S., Preparation and functional characterisation of fish skin gelatin and comparison with commercial gelatin. International Journal of Food Science & Technology 2013, 48, 1093-1102. 39. Ninan, G.; Joseph, J.; Aliyamveettil, Z. A., A comparative study on the physical, chemical and functional properties of carp skin and mammalian gelatins. J Food Sci Technol 2014, 51, 2085-2091. 40. Ktari, N.; Jridi, M.; Nasri, R.; Lassoued, I.; Ayed, H. B.; Barkia, A.; Nasri, M., Characteristics and functional properties of gelatin from zebra blenny (Salaria basilisca) skin. LWT-Food Science and Technology 2014, 58, 602-608. 41. Kim, S. K., Marine cosmeceuticals. Journal of cosmetic dermatology 2014, 13, 56-67. 42. Srikanya, A., A Study on Optimization of Fish Protein Hydrolysate Preparation by Enzymatic Hydrolysis from Tilapia Fish Waste Mince. Int. J. Curr. Microbiol. App. Sci 2017, 6, 3220-3229. 43. Yi, J.; De Gobba, C.; Skibsted, L. H.; Otte, J., Angiotensin-I converting enzyme inhibitory and antioxidant activity of bioactive peptides produced by enzymatic hydrolysis of skin from grass carp (Ctenopharyngodon idella). International Journal of Food Properties 2017, 20, 1129-1144. 44. Balti, R.; Bougatef, A.; Sila, A.; Guillochon, D.; Dhulster, P.; Nedjar-Arroume, N., Nine novel angiotensin I-converting enzyme (ACE) inhibitory peptides from cuttlefish (Sepia officinalis) muscle protein hydrolysates and antihypertensive effect of the potent active peptide in spontaneously hypertensive rats. Food chemistry 2015, 170, 519-525. 45. Lafarga, T.; Wilm, M.; Wynne, K.; Hayes, M., Bioactive hydrolysates from bovine blood globulins: Generation, characterisation, and in silico prediction of toxicity and allergenicity. Journal of Functional Foods 2016, 24, 142-155. 46. Minkiewicz, P.; Dziuba, J.; Iwaniak, A.; Dziuba, M.; Darewicz, M., BIOPEP database and other programs for processing bioactive peptide sequences. Journal of AOAC International 2008, 91, 965-980. 47. Fu, Y.; Young, J. F.; Løkke, M. M.; Lametsch, R.; Aluko, R. E.; Therkildsen, M., Revalorisation of bovine collagen as a potential precursor of angiotensin I-converting enzyme (ACE) inhibitory peptides based on in silico and in vitro protein digestions. Journal of Functional Foods 2016, 24, 196-206.
Next Patent: A PARTICLE DETECTION DEVICE AND A METHOD FOR DETECTING PARTICLES