Risks in Raw Meat Industry

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Samira SARTER , Philippe DANIEL

CIRAD -UMR Qualisud

Institut des Molécules et des Matériaux du Mans

IMMM UMR CNRS 6283

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Food safety risks

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Salmonella spp.

 Raw meat sold in market: Porc 39-64%; chicken 42-49-53%; beef 62%  Resistance in meat: Porc 50-73% ; Chicken 45%

 Tetracycline, sulphonamide, steptomycin, ampicillin, chloramphenicol,

trimethoprim, nalidic acid

 Multiresistance : 21-56% of isolates

 7-9 antibiotics: 15% / 10-13 antibiotics: 8%

 Multiresistant Salmonella from food or food-producing animals are

common in different countries:

 Malaysia 49-75% (n=88)  Thailand 44-66% (n=342)  Vietnam 21-56% (n=180)

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Listeria monocytogenes

 EU rejections: Filet Pangasius (8 notifications 2010; 17 en 2009)

Campylobacter spp.

 Chicken sold in market: 15.3%

 Chicken : 95% of strains are resistant to fluoroquinolones (critical AB)

Escherichia coli : a reservoir

 Resistance: 84% of isolates of beef, poultry, porc

 Resistance to fluoroquinolones: 16-21% of isolates, mainly in chicken

samples (52-63%)

 Multiresistant E. coli (n=99) in raw meat:

 89.5% in chicken meat  95% in chicken faeces  75% in pork meat isolates

Garin et al. IJFM 2012; Thi Thu Hao Van et al. IJFM 2012; Truong Ha Thai et al. IJFM 2012; Thi Thu Hao Van et al. AEM 2007; Thi Thu Hao Van et al. IJFM 2008.

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 Food Safety Objectives: "the maximum frequency and/or concentration

of a hazard in a food at the time of consumption that provides or contributes to the appropriate level of protection (ALOP)".

 To ensure that an FSO is met, it is required to set Performance Objectives

which correspond to the levels that must be met at earlier steps in the food chain before consumption.

 FSOs and POs must be achievable by the application of good practices

(GAP, GHP, GMP) and HACCP

 Microbiological Criteria can be used to define the microbiological quality

of raw materials, food ingredients, and end-products at any stage in the food chain.

Need for accurate, rapid and sensitive methods for detection and quantification of microbial hazards

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Standard methods for pathogen identification

AFNOR ISO 6579:2002 Identification of Salmonella spp Phenotypic methods Immunological methods (ELISA) Molecular methods (PCR) Biochemical methods Identification

Time depending on method

25g of sample Isolement XLD + XLT4 Incubation Pre enrichement Incubation in BPW Selective enrichment RVS + MKTTn

2 - 4 days _{Many hours}

Incubation Agar plate

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Applications of Raman

spectroscopy to bacteria

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Principles of Raman spectroscopy

Scattered radiations Interaction with a sample

monochromatic visible radiation : Laser ω₀, λ₀

Inelastic process

Sir Chandresekhara Venkata RAMAN

1888-1970 Raman effect gives the

vibrational signature of any kind of materials 600 800 1000 1200 1400 1600 1800 -0.02 0.00 0.02 0.04 0.06 0.08 0.10 0.12 0.14 0.16 0.18 int ensi ty (u. a) Wavelength (cm-1)

Advantages of the technics:

- Fingerprint technics

- No preparation of the sample - Non invasive technics

- Non destructive technics - Qualitative or quantitative

Source : ISI Web of Science – January 2014 – Key words: Raman, bacter*

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- Single-cell analysis of bacteria

Raman study of bacteria

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Pongsit Tangcananurak

Work done in the framework of Franco-Thai Program in 2008 - Investigation of

microcolonies and characterisation of heterogeneity

L.P. Choo-Smith et al, Applied and environmenetal microbiology, 2001

z coordinate

x coordinate

A B

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Interprétation of the spectrum: fingerprint technique

Nucleic acids Proteins

Carbohydrates Lipids

Raman study of bacteria

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507 : Carbohydrate C-O-C 652 : Tyrosine (Acide Aminé) 727 : Adénine (ADN)

872 : Tyrosine (Acide Aminé) 1037 : Lipides

955: Lipides

1240 : amide III 1323 : δ(CH2)

1377 : Symm Stretch (CON-), δ(CH2) 1464 : mono-oligosaccharides 1580 : ADN 1771 : Ester No m br e d’ onde Exemple of E-coli

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11 0,5 to 3 µm

Allow to distinguish between types of bacteria

Salmonelle Staphylococcus Pseudomonas Streptococcus Escherichia coli Bacillus subtilis Gram -Gram + Salmonella Staphylococcus Pseudomonas Streptococcus Escherichia coli Bacillus subtilis Gram -Gram + Bacteria wall B aci ll us subt il is S taphyl ococcus E scher ichi a col i P seudom onas S al m onel la H ét ér ogénéi té 0 0.2 0.4 0.6 0.8 1 Ward’s algorithm Gammes spectrales 400-1800 cm-1

Kengne-Momo, R P; Lagarde, F; Daniel, P et al, Biointerphases – Raman shift cm-1 Type de liaison 1630 ; 1705 Lipides insaturés 1630 ; 1705 Amide I 1440 Amide II 1240 Lipides 1100 Amide III 980 ; 1002 Phénylalanine 850 Tyrosine 770 Acides nucléiques 460 ; 590 Carbohydrates Raman shift cm-1 Type de liaison 1630 ; 1705 Lipides insaturés 1630 ; 1705 Amide I 1440 Amide II 1240 Lipides 1100 Amide III 980 ; 1002 Phénylalanine 850 Tyrosine 770 Acides nucléiques 460 ; 590 Carbohydrates

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600 800 1000 1200 1400 1600 1800 -0,02 0,00 0,02 0,04 0,06 0,08 0,10 0,12 0,14 0,16 0,18 in ten si té ( u. a) nombre d'onde (cm-1)  Latence phase  Exponential phase  Stationnary phase A c ides nuc léi q ues P hény lal a ni n e Li pi des C ar bohy dr at e s A m id e III A c ides nuc léi q ues Li pi des A m ide I I A m ide I , Li pi des croissance de VH en milieu VH à 25°C, 1% 0 0,5 1 1,5 2 2,5 3 3,5 4 4,5 0 100 200 300 400 500 600 temps (min) de ns it é opt

ique Latence phase

Exponential phase

Stationnary

phase

Raman study of bacteria by Raman spectroscopy

vs growth phases

L. Bendriaa, PhD Thesis , 2005

Frequency range used for classification: 1450-1750 cm-1

« Rather easy» distinction between young bacteria and old bacteria

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Functionalized surfaces for

detection of pathogenic

microorganisms

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Alternative method

Biosensor based on a « double check procedure » : (1) Specific capture of microorganisms

(2) Recognition by Raman spectroscopy

600 800 1000 1200 1400 1600 1800 -0.02 0.00 0.02 0.04 0.06 0.08 0.10 0.12 0.14 0.16 0.18 int ensi ty (u. a) Wavelength (cm-1) Specific functionalized surface Raman spectroscopy analysis Identification via spectra recognition 14 B aci ll us subt il is S taphyl ococcus E scher ichi a col i P seudom onas S al m onel la H ét ér ogénéi té 0 0.2 0.4 0.6 0.8 1 Ward’s algorithm Statistical data analysis

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600 800 1000 1200 1400 1600 1800 -0.020.00 0.02 0.04 0.06 0.08 0.10 0.12 0.14 0.16 0.18 () b d' d ( 1) 600 800 1000 1200 1400 1600 1800 -0.020.00 0.02 0.04 0.06 0.08 0.10 0.12 0.14 0.16 0.18 () b d' d ( 1) 600 800 1000 1200 1400 1600 1800 -0.020.00 0.02 0.04 0.06 0.08 0.10 0.12 0.14 0.16 0.18 () b d' d ( 1) 600 800 1000 1200 1400 1600 1800 -0.020.00 0.02 0.04 0.06 0.08 0.10 0.12 0.14 0.16 0.18 () b d' d ( 1) Raman

Quartz crystal microbalance

detection

Exemple: Gold surface functionalisation with parabenzenesulfonyle chloride

S O O O S O S O O O S O S O OO S O Cl Cl S O OO S O Cl Cl

Synthesis of specific surfaces of gold

with chemical modifications Protein A _Antibody

Antibody – antigen specific recognition

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16 QCM monitoring Raman characterization IgG(1g/l) Prot A (50 mg/l) 2 hours S O O O S O Protein A Antibody -1000 -750 -500 -250 0 0 500 1000 1500 2000 Time (s) F (H z ) PrA S-IgG 15 96 15 43 14 69 13 10 11 17 10 67 10 00 82 3 70 1 63 8 55 1 48 3 0 1 2 A bi tr ar y Un it s 3 4 5 400 600 800 1000 1200 1400 1600 1800 2000 Wavenumber (cm-1) PrA on Au 14 87 14 44 13 00 11 30 99 3 69 9 60 3 53 9 44 1 PrA + S-IgG on Au 15 96 15 43 14 69 13 10 11 17 10 67 10 00 82 3 70 1 63 8 55 1 48 3 0 1 2 A bi tr ar y Un it s 3 4 5 400 600 800 1000 1200 1400 1600 1800 2000 Wavenumber (cm-1) PrA on Au 14 87 14 44 13 00 11 30 99 3 69 9 60 3 53 9 44 1 PrA + S-IgG on Au Fluorescence image

Kengne-Momo, R P ; Daniel, P; Lagarde, F et al International Journal of Spectroscopy

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QCM monitoring Raman characterization 0 500 1000 1500 2000 2500 -300 -250 -200 -150 -100 -50 0 50 Anti-IgG (1,07g/l)

Functionalization procedure also possible on other type of substrate :

- Polyethylene traited by plasma - Functionalized Polyurethane

- Systems including nanoparticles

(magnetic, silver, gold: SERS effect) 0

1 2 A bi tr ar y Un it s 3 400 600 800 1000 1200 1400 1600 1800 2000 Wavenumber (cm-1) 15 90 14 46 13 10 11 22 10 56 99 2 93 1 68 3 63 0 55 1 0 1 2 A bi tr ar y Un it s 3 400 600 800 1000 1200 1400 1600 1800 2000 Wavenumber (cm-1) 15 90 14 46 13 10 11 22 10 56 99 2 93 1 68 3 63 0 55 1 Raman spectra (785 nm, 10 mW) of Salmonella immobilized on functionalised Au surface

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 Develop a detection kit based on Raman spectroscopy for specific

pathogens in food (model and food matrix)

 Target specific resistant bacteria, and try to explore the mechanisms of

actions (critical antibiotics)

 Screening of resistant strains along the food chain/environment

 Research at the interface between physics and chemistry of materials

Institute for Molecules and Materials of Le Mans

Department of solid state physics:

- Physics of advanced materials, Nanomaterials, Surface functionalization

- Multiscale and multitime elaboration and characterization technics.