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DEPARTMENT for ENVIRONMENT, FOOD and RURAL AFFAIRS CSG 15Research and Development

Final Project Report(Not to be used for LINK projects)

Two hard copies of this form should be returned to:Research Policy and International Division, Final Reports UnitDEFRA, Area 301Cromwell House, Dean Stanley Street, London, SW1P 3JH.

An electronic version should be e-mailed to [email protected]

Project title Conventional vs Capillary electrophoresis of RFLP fragments and PCR products for sensitive and rapid subtyping of Salmonella

DEFRA project code OZ0311

Contractor organisation and location

Central Science Laboratory, DefraSand HuttonYork, YO41 1LZ

Total DEFRA project costs £ 373,348.36

Project start date 01/06/99 Project end date 31/03/04

Executive summary (maximum 2 sides A4)

Worldwide, bacteria belonging to the genus Salmonella are important human and animal pathogens. There are over 2000 different serotypes of Salmonella of which the majority belong to subspecies I. Consequently, comprehensive typing of Salmonella is complicated. Epidemiological investigations have been based traditionally on phenotypic characteristics and patterns of resistance to antimicrobials. Increasingly, molecular typing methods have been introduced based on characterisation of the genotype of the organism.

The objective of this project was to compare different molecular typing techniques in combination with two electrophoretic techniques (conventional gel and capillary electrophoresis) for molecular subtyping of Salmonella enterica serovars from animal, human and food or feed sources. Fluorescent Amplified Restriction Fragment Length Polymorphism (f-AFLP), Random Amplified Polymorphic DNA (RAPD), Repetitive Extragenic Palindromic Sequences (REP) and Enterobacterial Repetitive Intergenic Consensus (ERIC) polymerase chain reaction (PCR) and restriction digestion based methods such as Pulsed-field Gel Electrophoresis (PFGE), Restriction Fragment Length Polymorphism (RFLP) were investigated.

AFLP analysis is a broadly applicable genotyping method with high degrees of reproducibility and discriminatory power. Several applications in taxonomy, diagnostics, and epidemiology have already been realised. The good reproducibility of AFLP may allow compilation of a database of genotypes and the exchange of data between laboratories. This requires the use of standardised reagents and protocols and international strain depositories. Earlier project work concentrated on development of robust f-AFLP protocols. In this work two different AFLP methods were compared, one based on the method developed by Aarts et al., 1998 and one developed by Scott et al., 2001. We found that the different AFLP methods discriminated similar Salmonella serovars differently. From this, it was concluded that different AFLP methods may be appropriate for discrimination of different serovars.

The main emphasis in the final project year concentrated on the f-AFLP technique and its potential to identify unambiguously Salmonella isolates in an outbreak situation. Results obtained showed that discrimination within the

CSG 15 (Rev. 6/02) 1

Projecttitle

Conventional vs Capillary electrophoresis of RFLP fragments and PCR products for sensitive and rapid subtyping of Salmonella

DEFRAproject code

OZ0311

major serovars from animal origin was around 90% for the majority of strains. This indicated some lack of inter-serovar discrimination. Similar results have been obtained previously for the major serovars from human, food and feed. For representatives of the minor serovars there was a slightly better discrimination for isolates derived from animal sources (80% similarity) than for those from human, food and feed (70–80% similarity). The main concern with the technique was its reproducibility. Throughout the project it became evident that there was a need to standardise the methodology to eliminate data variability as far as reasonably possible. In addition, movement of electrophoresis equipment prior to the final project year within the laboratory had an impact on data produced afterwards. Despite this, we were able to correctly identify 53% and a further 23% with a second option from a set of 30 unknown strains based on investigations done during the last project year. This indicates the potential of f-AFLP to be successfully applied for outbreak recognition.

In our investigation, the discriminatory power of f-AFLP and PFGE for the range of strains investigated were comparable. PFGE showed in our investigation a higher degree of discrimination amongst S. typhimurium. A number of strains were similar at the 70% level. However, representatives of the phage type DT104 were not differentiated and showed similarity of 100%. PFGE showed some intra-serovar discrimination within the following minor serovars; S. bredeney, S. schwarzengrund, S. heidelberg, S. agona, S. stanley, S. indiana, S. abony, S. chester, S. brandenburg, S. san-diego, S. stanleyville, S. reading and S. derby. However, some strains were not fully discriminated. This indicated that PFGE does not identify all Salmonella isolates unambiguously.

Our investigation revealed that the three PCR based techniques, random amplified polymorphic DNA (RAPD), repetitive extragenic palindromic sequences (REP) and enterobacterial repetitive intergenic consensus sequences (ERIC) PCR, discriminated at a serovar level, but displayed a lack of discrimination within serovars at the strain level.

The use of RFLP analysis has been documented for differentiation of Salmonella strains. It was found that the rare cutting restriction endonuclease SnaB1 produced sufficient DNA fragments in the 1000-7000bp region for RFLP comparison. Conventional agarose gel electrophoresis separation of digested genomic DNA gave poor fragment resolution, predominantly caused by DNA shear. This problem is commonly noted as a feature of resolution of genomic DNA fragments. The poor fragment resolution of the RFLP profiles made profile analysis complicated. As such, an unmodified RFLP protocol using an agarose separation platform may not be suitable for large epidemiological studies of Salmonella.

Capillary electrophoresis separation was evaluated as a method for separation of DNA fragments. The equipment used was an unmodified Biofocus 3000 capillary instrument (BioRad), which uses long, coated capillaries (75µm ID x 375µm OD x 24cm). DNA fragment separation was possible using covalently bonded, cross-linked linear polyacrylamide as the sieving mechanism. The best resolution for DNA fragment separation by capillary electrophoresis was obtained between 100bp and 700bp. Above 700bp resolution was lost and peak widening was experienced. The peak widening experienced using the unmodified Biofocus 3000 capillary instrument made capillary electrophoresis separation unsuitable for RFLP comparison.

In general it was found that DNA peaks were eluted after 10 minutes, with DNA fragments of 1500bp or more being eluted after 30 minutes. Elution times of 30 minutes per sample meant that capillary analysis was comparatively slower than agarose gel electrophoresis for analysis of more than 5 samples. Differences in migration times experienced both in the external standard data as well as internal standard data, made analysis of the capillary data difficult. Instrumentation drift and differences in buffer batches added to migration time variation. In order to evaluate the capillary data, it was necessary to devise a strategy for meaningful analysis. Taken together, capillary electrophoresis using the Biofocus 3000 format, may not be appropriate for epidemiological study. State-of-the–art capillary technology may help to eliminate problems such as instrumental drift and sample to sample variations.

Capillary electrophoresis detection of the DNA fragments was by U.V. absorption at 260nm. This detection method, was 10-fold less sensitive than ultra-violet detection of ethidium bromide stained DNA in agarose gels. Thus only the most concentrated DNA fragments were detected by capillary electrophoresis. This impacted on analysis of ERIC PCR amplification products and f-AFLP fragments, yielding far fewer peaks than expected through conventional analysis. This resulted in too few peaks for meaningful BioNumerics analysis and poor serovar discrimination for both techniques. Resolution of such problems for ERIC-PCR product analysis could involve use of a capillary electrophoresis instrument with higher sensitivity for DNA coupled with a DNA dye suitable for detection at 254nm. A second alternative may be to use concentrated DNA samples.

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DEFRAproject code

OZ0311

The sensitivity of the f-AFLP technique is due to incorporation of a fluorescent tag in the PCR stage of the methodology. The ABI PRISM 377 sequencer measures peaks of fluorescent intensity as the tagged DNA passes the fluorescent detector, enabling detection of tiny concentrations of DNA. Capillary electrophoresis detection, however, measures DNA concentration as a feature of increase in UV absorbance against time. It was found that UV absorbance was less sensitive than fluorescence detection as far fewer peaks were detected by capillary electrophoresis than by the ABI PRISM 377 sequencer. For direct comparisons to be made between the separation of f-AFLP fragments by the ABI 377 sequencer and separation of f-AFLP fragments by capillary electrophoresis it would be necessary to establish a relationship between fluorescence and DNA concentration. The best method for making such comparisons would be to fit a fluorescence detector to the capillary electrophoresis machine. Once this has been carried out then further work is required to determine whether capillary separation has better resolution than that achieved by the ABI 377 sequencer. The capillary data obtained for f-AFLP indicated that there were f-AFLP fragments of greater than 500bp. Extending the calibration range of the ABI PRISM 377 to greater than 500bp may enable further differentiation of the Salmonella strains.

In conclusion, we found that not all Salmonella strains are discriminated by one specific method. Our investigations revealed that PFGE and f-AFLP are the most powerful and promising techniques for differentiation to strain level. Results from f-AFLP indicated a need to standardise and carefully interpret data by relying on internal standards and at least triplicate analysis. In addition, we found that different AFLP methods may be required for unambiguous differentiation of different Salmonella serovars. Further work investigating this aspect of f-AFLP typing of Salmonella is required. Capillary electrophoresis using the Biofocus 3000 format, may not be appropriate for such a large epidemiological study. The use of state-of-the–art capillary technology, however, may help to eliminate problems such as instrumental drift and sample to sample variations.

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DEFRAproject code

OZ0311

Scientific report (maximum 20 sides A4)1. Introduction

Salmonella is one of the most important pathogen involved in human foodborne illness in the developed world. The majority of cases of human salmonellosis are due to the consumption of contaminated egg, poultry, pork, beef and milk products. Salmonella control is therefore necessary at all the key stages of food production to ensure safe products for consumers. This control requires rapid and reliable methods in the detection, isolation, characterisation and typing of Salmonella isolates. Serotyping is the most common method used to differentiate Salmonella strains. Classically, serotyping was used to divide Salmonella into distinct species based on their serotypes. Although the majority of outbreaks in livestock are caused by a selected number of serotypes, serotyping is not an adequate method for determination of the source of contamination during an outbreak. One subtyping method for epidemiological investigations of human and animal salmonellosis is phage typing. Phage typing has proven to be epidemiologically valuable in strain differentiation within a particular Salmonella serotype (Anderson et al., 1977; Ward et al., 1987). Differentiation of Salmonella isolates and sources of identification of foodborne outbreaks can be accomplished by using molecular typing techniques. These techniques can be restriction digestion or amplification based.Restriction based molecular typing techniquesPulsed field electrophoresis (PFGE) and other restriction fragment length polymorphism analysis (RFLP) techniques are based on DNA isolation and restriction fragment analysis. PFGE is a technique applied world-wide for bacterial typing and is the Gold Standard of the molecular typing methods because of its high discriminatory power and reproducibility. PFGE separates DNA under conditions of alternating polarity allowing for the resolution of DNA fragments nearly 20 times larger than those separated by traditional agarose gel electrophoresis. Macrorestriction fingerprinting based on profile patterns obtained by digestion of genomic DNA followed by pulsed-field gel electrophoresis (PFGE) has been used for the fingerprinting of Salmonella enterica for both national and international outbreaks. For most serotypes and phage types, PFGE has proved both discriminatory and highly reproducible. However, problems may arise in determining strain relationships when apparently closely related patterns have been generated but epidemiologic information is limited. Further possible drawbacks of PFGE may include the necessity to eliminate the involvement of plasmid DNA in the determination of profile types, and the ability of some serotypes to generate DNA suitable for enzymatic digestion when contained in agarose plugs (Sood et al., 2002). Amplification based molecular typing techniquesRandom amplified polymorphic DNA (RAPD) is a modification of the polymerase chain reaction (PCR) in which a single primer able to anneal and prime at multiple locations throughout the genome can produce a spectrum of amplified products. The resultant fingerprint can be of epidemiological value. The technique has been optimised for fingerprinting Salmonella isolates (Hilton et al., 1997).Repetitive extragenic palindromic (REP) elements and enterobacterial repetitive intergenic consensus (ERIC) sequences have been further used for genotyping of Salmonella isolates. It has been shown that these sequences can be utilised as efficient primer binding sites in the polymerase chain reaction to produce fingerprints of different bacterial genomes (Versalovic et al., 1991; Hulton et al., 1991; Johnson and Clabots, 2000).Amplified fragment length polymorphism (AFLP) fingerprinting is a polymerase chain reaction (PCR) based method in which restriction enzyme-generated DNA fragments are amplified and then visualised. Unlike other PCR methods, this approach does not require prior knowledge of the nucleotide sequences. AFLP differs from other techniques, such as randomly amplified polymorphic DNA (RAPD) fingerprinting, through the use of highly stringent PCR conditions. Such conditions contribute to elimination of inconsistencies between reactions. Fluorescent AFLP (f-AFLP) utilises a fluorescent dye-labelled primer to aid visualisation of amplification reactions. This methodology has proved to be reproducible and shown to have similar or higher discriminatory power than PFGE in genotyping S. enterica serovars (Savelkoul et al., 1999; Hu et al., 2002).Traditionally, separation of DNA fragments has been carried out by agarose gel electrophoresis. An alternative to analysis of DNA fragments in ethidium bromide stained gels is the use of capillary electrophoresis separation. Jorgenson and Lukacs (1981) first introduced capillary electrophoresis for the separation of charged molecules. The methodology has since been adapted for conventional electrophoresis applications, such as protein and DNA separation. The advantages of capillary electrophoresis in comparison to conventional electrophoresis are that separations may be carried out faster, cheaper and have better resolution of different relative molecular mass molecules (Issaq et al., 1997).

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DEFRAproject code

OZ0311

The objective of this project was to compare different molecular typing techniques for molecular subtyping of Salmonella spp. Pulsed-field Gel Electrophoresis (PFGE), Restriction Fragment Length Polymorhism (RFLP) and polymerase chain (PCR) based techniques such as Fluorescent Amplified Restriction Fragment Length Polymorphism (f-AFLP), Random Amplification of Polymorphic DNA (RAPD), Repetitive Extragenic Palindromic (REP) and Enterobacterial Repetitive Intergenic Consensus (ERIC) PCR were investigated. In the final project year particular emphasise was placed on the reproducibility of f-AFLP when using cells harvested from growth medium before and after passage through a meat matrix.Annual reports submitted after each project year contain detailed information regarding optimisation of the PCR based techniques, RFLP, capillary electrophoresis and PFGE for molecular identification of Salmonella isolates. The early work will be presented in the final report in summary, together with more detailed f-AFLP results and analysis of animal derived isolates, which was the emphasis of the final project year. Those data will be compared with results from human, food and feed isolates from the previous year.

2. Fluorescent amplified fragment length polymorphism (f-AFLP)

AFLP methods generate fingerprints from DNA without prior knowledge of the sequence. The method involves the following steps: (i) digestion of DNA with a rare and a frequent cutter restriction enzyme and (ii) subsequent ligation with a specific adapter to all restriction fragments. The resulting adapter-ligated fragments are templates for selective amplification with PCR primers directed at restriction-enzyme-specific target sequences on the adapters. The PCR primers can be labelled radioactively, and the fragments can be separated on sequencing gels. We have used an approach where the primers were labelled with fluorescent dye. This method has been previously applied for Salmonella enterica subsp. enterica serovars typing (Lindstedt et al., 2000; Desai et al., 2001).In this study we investigated a selection of major and minor S. enterica subsp. enterica serovars derived from animal sources. DNA was extracted and subjected to f-AFLP analysis on two independent occasions and results compared to assess reproducibility. Dendrogram traces that matched with the corresponding repeated isolate were compared with results obtained for major and minor serovars from human, food and feed origin a year before. In addition, we blindly selected 30 strains from the animal isolates and analysed them after growth in medium. They were further inoculated into fresh and frozen minced beef meat, isolated by using the current British Standard method (BS EN ISO 6579, 2002). The isolates obtained were grown in medium and subjected to f-AFLP analysis. The traces were compared for reproducibility and any potential effects relating to the food matrix. The ‘unknown’ isolates were identified, based on the database constructed from results from this project year. Identification was achieved using the similarity coefficient and dendrogram approach provided by the software.

2.1. Materials and Methods

2.1.1. Strains Animal derived isolates from serovars of S. enterica subsp. enterica have been kindly supplied by AFSSA (Paris, France) who supplied major and VLA (Weybridge, UK) who supplied minor serovars. Seven strains of S. hadar (501–507), 10 strains of S. typhimurium (491–500) and 5 strains of S. virchow (508–512) were analysed. One strain each of the following minor serovars was investigated: S. abony (486), S. adelaide (484), S. agama (456), S. agona (489), S. ajioba (490), S. alachua (482), S. albany (483), S. amager (450), S. anatum (476), S. arechararleta (477), S. arizonae (478), S. bareilly (481), S. binza (473), S. blockley (475), S. bovismorbificans (474), S. branderup (480), S. bredney (479), S. canstatt (461), S. caracus (460), S. cerro (462), S. chailey (465), S. coeln (464), S. corvallis (466), S. cubana (472), S. drypool (459), S. dublin (467), S. dusseldorf (471), S. durban (469), S. durham (463), S. eastbourne (468), S. eimsbuettel (458), S. emek (485), S. florida (488), S. fresno (457), S. give (455), S. grumpensis (470), S. guiena (453), S. haardt (446), S. haifa (447), S. hindmarsh (449), S. hvittingfoss (448), S. indiana (451), S. infantis (452), S. isangi (487), S. jukestown (444), S. kedougou (445), S. kentucky (454), S. krefeld (437), S. litchfield (440), S. liverpool (435), S. london (439), S. manhatten (434), S. marina (429), S. mbdanka (431), S. mgulani (403), S. minnesota (402), S. mississippi (436), S. munchen (443), S. munster (438), S. napoli (442), S. newington (441), S. newport (427), S. ohio (424), S. oranienberg (423), S. oslo (425), S. oukham (432), S. oxford (422), S. pomona (407), S. poona (413), S. richmond (417), S. rubislaw (415), S. ruiru (405), S. saint-paul (412), S. san-diego (433), S. schwarzengrund (410), S. sorenga (420), S. stanley (408), S. stanleyville (419), S. tees (421), S. tel-aviv (428), S. tel-el-kebir (401), S. tennessee (404), S. uganda (418), S. vinohrady (409), S. virginia (414), S. wandsworth (406), S. wangata (416), S. waycross (411), S. weltereden (400), S. worthington (430), S. zanzibar (426).

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DEFRAproject code

OZ0311

Minor animal derived serovars that were shown to cluster together following independent repeat analysis, were compared to f-AFLP fingerprints of minor serovars from human and food isolates prepared in the previous project year. These isolates were provided by the HPA (Colindale, London, UK) and are listed in Table 1.

Table 1. Minor human food or feed Salmonella enterica subspecies serovar isolates used for comparison.

Strain Serovar Strain ID† Origin O-group† Phage type†

Plasmid profile (bp)†

Antibiotic resistance†

Sal 208 S. amager S180897/0 Human E1 NT NT NTSal 206 S. anatum S180779/0 Human E1 NT NT $Sal 218 S. arecharaleta S181843/0 Human B - 1 $Sal 161 S. bareilly S179524/0 Human C1 + C4 - 50, 18 $Sal 133 S. blockley S179612/0 Human C2 + C3 - 6, 5 $Sal 194 S. bredney S181900/0 Human B - 4.6, 1 SuTmSal 253 S. caracas S180165 Dog Chew H NT 110, 60, 4.6, 4 $Sal 190 S. cerro S180099/0 Human K NT 70 $Sal 223 S. chailey S181722/0 Human C2 + C3 - 4 $Sal 219 S. coeln S181573/0 Human B - 80 ASuTmSal 202 S. dublin S180722/0 Human D1 NT 50 $Sal 222 S. duesseldorf S181625/0 Human C2 + C3 - 55 $Sal 205 S. durban S180932/0 Human D1 NT NT NTSal 189 S. durham S180290/0 Human G1 + G2 NT NT NTSal 203 S. eastbourne S181054/0 Human D1 NT - $Sal 198 S. eimsbuettel S180680/0 Human C1 + C4 - 30 $Sal 174 S. emek S179763/0 Human C2 + C3 - 58, 3 ACKSSuSpTmSal 231 S. florida S181478/0 Human H NT 80 $Sal 302 S. fresno S180690/0 UNK - - - -Sal 128 S. indiana S179750/0 Human B - - $Sal 264 S. kedougou S180471 Cockles G1 + G2 NT 1 $Sal 162 S. kentuckey S179554/0 Human C2 + C3 - - $Sal 139 S. marina S181205/0 Human Y NT - $Sal 137 S. pomona S181367/0 Human M NT 80 $Sal 306 S. poona S185890 Animal G1 + G2 NT - NTSal 280 S. rubislaw S181356 Pepper F NT - $Sal 129 S. saint-paul S179684/0 Human B - 4,1 ACSSuSpTTmSal 287 S. sorenga S182257 Pig Feed N NT 10, 4, 3.8, 1 $Sal 167 S. stanley S180006/0 Human B - - AKSSuT TmNeSal 217 S. stanleyville S181650/0 Human B - - $Sal 289 S. tees S143962 Animal Feed I NT 2 $Sal 230 S. tel-el-kebir S181153/0 Human G1 + G2 NT NT NTSal 228 S. uganda S181466/0 Human E1 NT NT NTSal 295 S. wandsworth S188289 Fish Tank Water Q NT 70, 3.8 $Sal 235 S. wangata S181946/0 Human D1 NT NT NTSal 296 S. waycross S159518 Human S NT - $Sal 238 S. vinohrady S181963 Human NT NT NT NT†The strains and the corresponding information were kindly provided by Dr John Threlfall, Laboratory for Enteric Pathogens, Health Protection Agency, Central Public Health Laboratory, Colindale, London, UK. NT: not tested, ‘-‘: no information available. $: sensitive, A: Ampicillin, C: Chloramphenicol, K: Kanamycin, Ne: Neomycin, S: Streptomycin, Su: Sulphonamides, Sp: Spectomycin ,T: Tetracycline, Tm: Trimethaprim.

2.1.2. Wizard Genomic DNA extractionDNA was extracted from overnight cultures in Nutrient broth (NB; Oxoid) using a modified protocol of the Wizard Genomic DNA Purification Kit (Promega Life Sciences, Southampton, UK). The Salmonella strains were grown aerobically at 37°C for 18 h in Nutrient broth. Cells from 1.0ml of overnight culture were harvested by centrifugation at 13,000xg for 10 min at room temperature. The supernatant was discarded and cell pellet retained. The cell pellet was

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OZ0311

gently resuspended in 600l of Nuclei Lysis solution (Promega) and incubated at 80ºC for five minutes to lyse the cells. RNase solution (3l) and 80l of pronase (100g ml-1) were added to the lysate and mixed by inversion. The lysate mixture was incubated for one hour at 37 °C, and cooled to room temperature. Protein precipitation solution (200l) was added to the pronase and RNase treated lysate, and the mixture vortexed for twenty seconds prior to incubation on ice for five minutes. Centrifugation at 13,000xg for 10 min pelleted the precipitated protein, the protein free supernatant was transferred to a sterile 1.5ml eppendorf tube. The decanted supernatant was added to isopropanol (600l) at room temperature and was mixed by inversion until genomic DNA formed a visible mass. Genomic DNA was harvested by centrifugation at 13,000xg for 5 min, the supernatant was decanted, and genomic DNA pellet drained. The genomic DNA pellet was resuspended by inversion in ethanol (600l of a 70% v/v solution). The cleaned genomic DNA was centrifuged at 13,000xg for 2 min and the supernatant decanted. The DNA pellet was air-dried for 20 min. Genomic DNA was resuspended in 100l of rehydration solution and incubated for one hour at 65oC prior to quantification using the Gene-Quant DNA calculator (Pharmacia).

2.1.3. Protocol for f-AFLP analysis of SalmonellaThe method and selective primer combinations for f-AFLP analysis were derived either from the protocol published by Aarts et al. (1998) or the method published by Scott et al. (2001). The f-AFLP method consists of four main steps: (1) Digestion of total cellular DNA with one rare cutter restriction enzyme and one frequent cutter restriction enzyme (2) Ligation of half site-specific adaptors (3) Selective amplification of these fragments with two PCR primers, one of which is fluorescent dye-labelled (4) Electrophoretic separation of the PCR products on a denaturing polyacrylamide gel (Janssen et al., 1996).

2.1.3.1. Restriction DigestionThe first step of the AFLP procedure is a restriction digest. For micro-organisms that have a <65% G + C content, a sequential digest using the Promega supplied enzymes EcoRI and Tru9I was recommended. This was carried out as a double digest using a restriction buffer compatible with both enzymes. Sterile Sigma water (8.8l), Buffer C (5.0l), BSA (0.2l), Template DNA (5.0l), EcoRI restriction enzyme (0.5l) and Tru9I restriction enzyme (0.5l) were added together, gently mixed and then incubated in a water bath for two hours at 37 °C. A second incubation was carried out for a further fifteen minutes at 70 °C to allow Tru9I digestion.

2.1.3.2. Annealing and ligation adaptor pairsThere are two sets of adaptor pairs used in f-AFLP; an MseI adaptor pair and an EcoRI adaptor pair. The adaptor pairs were pre-treated prior to use, to enable annealing and ligation to the DNA template.

2.1.3.2.1. Pre-treatment of adaptor pairsThe adaptor pairs were heated in a hot block at 95°C, for five minutes, and then cooled to ambient temperature for ten minutes. The adaptors were centrifuged for ten seconds at 1400g, and stored in a -20°C freezer until required.

2.1.3.2.2. Ligation of adaptor pairsSterile Sigma water (1.67l), Ligase Buffer (1l), EcoRI Adaptor (1l of a 2mM stock solution), MseI Adaptor (1l of a 20mM stock solution), Prepared template DNA (6l) and T4 DNA Ligase (0.33l) were added to a sterile microcentrifuge tube to give a final volume of 11l. The ligation mixture was incubated for three hours at 37 °C and products stored at 4°C until required.

2.1.3.3. Selective amplificationThe purpose of the selective PCR amplification was to incorporate a fluorescent dye-label into the amplified DNA product. This enabled band detection on the ABI 377 DNA sequencer. The ligation product was diluted 1:2 with sterile water and used as a template in selective PCR. To 1.5l of diluted DNA, the following mixture was added: 7.5l PCR core mix (AB Gene), 0.5l of EcoRI-AA (JOE) primer (1M stock solution) and 0.5l of MseI-O Primer (5M stock solution). (For the method described by Scott et al., 2001, the above primers were replaced with EcoRI-O (FAM) and MseI-AT). The PCR master mix was gently mixed and amplification was carried out using the following PCR amplification cycle:

Number of Cycles Cycle sequence1 94°C for 2 minutes10 94°C for 20 seconds

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OZ0311

66°C* for 30 seconds 72°C for 2 minutes

20 94°C for 20 seconds 56°C for 30 seconds 72°C for 2 minutes

1 60°C for 30 minutesHOLD 4°C

The annealing temperature * was lowered by 1°C every cycle.

2.1.3.4. Preparation of loading buffer for the ABI PRISM 377Deionised formamide (1.25µl), blue dextran in 50mM EDTA loading solution (0.25µl) and GeneScan-500 ROX size standard (0.5µl) were combined and mixed in sufficient quantity for the number of samples. Loading buffer mix (2µl) was added to 1µl of selective amplification product in individual tubes. This mixture was heated to 95°C for five minutes and immediately chilled on ice.

2.1.3.5. Electrophoretic separation and analysisThe prepared amplification product (1.5µl) was loaded onto a 5% denaturing polyacrylamide gel on an ABI PRISM 377 DNA automated sequencer (Applied Biosystems). The electrophoresis was performed at 51°C using 1X TBE running buffer, for three hours at 2.5kV. Representative electropherograms of fluorescent dye-labelled AFLP products were imported in to the BioNumerics software (Applied Maths) for analysis using the ABICON programme.

2.1.3.4. Inoculation and isolation of Salmonella strains from meat 30 Salmonella strains were randomly selected from a panel of 91 minor and 22 major animal derived isolates. Strains were maintained at –80°C on cryogenic beads. One bead of each strain was transferred onto a Columbia Blood agar (CBA) plate that was incubated overnight at 37°C. Cultures were checked for purity. Nutrient broth (10ml) was inoculated with each salmonella strain and incubated overnight at 37°C.Amounts of fresh minced beef (25g) and of pre-prepared frozen minced beef (25g) were inoculated with approximately 104 cfu from the overnight cultures. The rest of the cultures were used for DNA extraction and subsequent f-AFLP analysis. Isolation of Salmonella from meat samples followed BS EN ISO (2002) using buffered peptone water (BPW) and xylose lysine deoxycholate (XLD) only. Each sample was stomached with 225ml BPW for two minutes and incubated overnight at 37°C in non-selective enrichment. The non-selective enrichment (100µl) was transferred into 10 ml Rappaport Vassiliadis with soya (RVS) broth and incubated overnight at 41.5°C. The selective enrichment RVSs was streaked onto XLD and incubated overnight at 37°C. Suspect colonies were streaked onto nutrient agar (NA) and incubated at 37 °C overnight. For confirmation ‘O’ and ‘H’ agglutination, oxidase and API 20E tests were carried out. Salmonella strains were retrieved from all meat samples and fresh preparations from the NA used for confirmation. The strains were grown in NB overnight at 37°C for DNA extraction and subsequent f-AFLP analysis.

2.1.3.5. Prediction of unknown strainsUnknown isolates were identified by a dendrogram and individual comparison approach.

2.1.3.5.1. Identifying unknown isolates using BioNumercis softwareAll data from animal derived Salmonella isolates (Table 1) were selected within the database. From the database, the unknown isolate to be identified was also selected. A new comparison of all the selected entries was created. The unknown isolate to be identified was selected and ranked based on similarity against all other isolates. The unknown isolate that was selected, stands on the top and all the other entries in the comparison are arranged by decreasing similarity with that entry. The similarity values are displayed in the matrix panel alongside the isolate names. The ‘arrange entries by similarity’ function has to be repeated for each individual unknown sample to be identified. The program uses the similarity coefficient, which is specified by the software.

2.1.3.5.1. Identifying unknown isolates using dendrogramsAll the Salmonella strains from the current work were selected and included in a dendrogram (all possible strains the unknowns could be). The unknown isolates were also selected. The similarity coefficient selected was, the Pearson product-movement correlation coefficient, and the dendrogram type selected was the unweighted Pair Group Method using Arithmetic averages (UPGMA). The fingerprints were added to the cluster analysis, and the full dendrogram displayed in print preview window. Dendrograms were pasted into Word from the BioNumerics software for printing.

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DEFRAproject code

OZ0311

Dendrograms were studied to see where the unknown isolates fell among the known isolates in the clustering, and how similar they were.

2.2. Results

2.2.1. Comparability of f-AFLP analysis when analysed on a separate occasionTwenty-two major and 91 minor serovars from animal sources were grown and their DNA was extracted followed by f-AFLP analysis on two separate and independent occasions. The results were compared for their degree of similarity and by dendrogram analysis. Table 2 shows the similarity between duplicate samples analysed on separate occasions and the similarity between the internal corresponding standards (ROX).

Table 2. Similarity in percentage between replicate analysis of animal derived minor Salmonella enterica subsp. enterica serovars and the internal sample standards for f-AFLP analysis.

Sal Number Salmonella serovar Date of original gel

Date of repeat gel

Similarity between duplicate

strains (%)

Duplicates clustered in dendrogram

Similarity between ROX duplicates (%)

400 S. weltereden 28/08/03 11/09/03 83.22 X 96.86401 S. tel-el-kebir 28/08/03 11/09/03 91.37 ✓ 87.94402 S. minnesota 28/08/03 11/09/03 83.77 X 81.36403 S. mgulani 28/08/03 11/09/03 88.15 X 79.71404 S. tennessee 28/08/03 11/09/03 88.63 X 79.97405 S. ruiru 28/08/03 11/09/03 89.18 X 78.43406 S. wandsworth 28/08/03 11/09/03 90.43 ✓ 74.39407 S. pomona 28/08/03 11/09/03 92.9 ✓ 77.86408 S. stanley 28/08/03 11/09/03 92.83 ✓ 80.91409 S. vinohrady 28/08/03 11/09/03 86.88 ✓ 78.13410 S. schwarzengrund 28/08/03 11/09/03 82.79 X 77.86411 S. waycross 28/08/03 11/09/03 82.43 ✓ 72.95412 S. saint-paul 28/08/03 11/09/03 90.09 ✓ 68.81413 S. poona 28/08/03 11/09/03 86.5 ✓ 82.26414 S. virginia 28/08/03 11/09/03 87.16 X 77.08415 S. rubislaw 28/08/03 11/09/03 87.33 ✓ 80.42416 S. wangata 28/08/03 11/09/03 66.84 ✓ 54.03417 S. richmond 28/08/03 11/09/03 76.45 X 78.15418 S. uganda 28/08/03 11/09/03 83.41 ✓ 79.19419 S. stanleyville 28/08/03 11/09/03 85.87 ✓ 82.75


Date of repeat gel


strains (%)



420 S. sorenga 28/08/03 11/09/03 82.01 ✓ 79.17421 S. tees 28/08/03 11/09/03 81.16 ✓ 80.98422 S. oxford 28/08/03 11/09/03 78.59 X 80.66424 S. ohio 28/08/03 11/09/03 82.71 ✓ 74.47425 S. oslo Fail Fail426 S. zanzibar 29/08/03 12/09/03 75.79 X 98.57427 S. newport 29/08/03 12/09/03 78.82 X 83.39

CSG 15 (Rev. 6/02) 9

Projecttitle


DEFRAproject code

OZ0311

428 S. tel-aviv 29/08/03 12/09/03 75.05 ✓ 99.53429 S. marina 29/08/03 12/09/03 79.54 ✓ 98.79430 S. worthington 21/01/03 12/09/03 58.28 X 87.83431 S. mbdanka 29/08/03 12/09/03 83.73 X 99.57432 S. ouakham 29/08/03 12/09/03 80.98 X 99.67433 S. san-diego 29/08/03 12/09/03 49.89 X 88.74434 S. manhatten 21/01/03 12/09/03 48.51 X 89.01435 S. liverpool 29/08/03 12/09/03 85.47 X 99.7436 S. mississippi 29/08/03 12/09/03 81.64 X 94.62437 S. krefeld Fail Fail438 S. munster 29/08/03 12/09/03 47.25 X 99.58439 S. london 29/08/03 12/09/03 55.26 X 99.48440 S. litchfield 29/08/03 12/09/03 77.25 X 99.49441 S. newington 29/08/03 12/09/03 63.79 X 99.04442 S. napoli 29/08/03 12/09/03 45.45 X 99.23443 S. munchen 21/01/03 12/09/03 60.21 X 89.75444 S. jukestown 21/01/03 12/09/03 65.07 X 97.96445 S. kedougou 29/08/03 12/09/03 86.24 ✓ 99.32446 S. haardt Fail Fail447 S. haifa 29/08/03 12/09/03 82.95 X 96.93448 S. hvittingfoss 29/08/03 12/09/03 87.3 ✓ 98.49449 S. hindmarsh 04/09/03 19/09/03 91.21 ✓ 98.85450 S. amager 04/09/03 19/09/03 91.95 ✓ 93.01451 S. indiana 04/09/03 19/09/03 84.79 ✓ 90.29452 S. infantis 04/09/03 19/09/03 76.98 ✓ 89.51453 S. guiena 04/09/03 19/09/03 84.96 ✓ 89.13454 S. kentucky 04/09/03 19/09/03 90.02 ✓ 88.18455 S. give 04/09/03 19/09/03 84.92 X 88.63456 S. agama 04/09/03 19/09/03 80.47 X 87.69457 S. fresno 04/09/03 19/09/03 88.15 ✓ 90.23458 S. eimsbuettel 04/09/03 19/09/03 78.63 ✓ 80.47459 S. drypool 04/09/03 19/09/03 77.64 X 98.57460 S. caracus 04/09/03 19/09/03 86.79 ✓ 89.39


Date of repeat gel


strains (%)



461 S. canstatt 04/09/03 19/09/03 84.9 X 90.47462 S. cerro 04/09/03 19/09/03 91.81 ✓ 90.83463 S. durham 04/09/03 19/09/03 82.98 ✓ 90.89464 S. coeln 04/09/03 19/09/03 85.83 ✓ 89.09465 S. chailey 04/09/03 19/09/03 88.04 ✓ 90.27466 S. corvallis 04/09/03 19/09/03 89.05 X 89.75467 S. dublin 04/09/03 19/09/03 92.93 ✓ 91.67468 S. eastbourne 04/09/03 19/09/03 89.77 ✓ 90.09469 S. durban 04/09/03 19/09/03 89.87 ✓ 88.44

CSG 15 (Rev. 6/02) 10

Projecttitle


DEFRAproject code

OZ0311

470 S. grumpensis 04/09/03 19/09/03 72.84 X 85.53471 S. duesseldorf 04/09/03 19/09/03 94.17 ✓ 88.07472 S. cubana 04/09/03 19/09/03 80.47 X 81.65473 S. binza 05/09/03 24/09/03 86.3 ✓ 97.91474 S. bovis morbificans 05/09/03 24/09/03 98.55 ✓ 99.44475 S. blockley 05/09/03 24/09/03 97.21 ✓ 99.69476 S. anatum 05/09/03 24/09/03 98.98 ✓ 99.77477 S. arechararleta 05/09/03 24/09/03 99.2 ✓ 99.5478 S. arizonae 38;261.253

SGIIIbb1205/09/03 24/09/03 99.68 ✓ 99.71

479 S. bredney 05/09/03 24/09/03 99.77 ✓ 99.74480 S. braenderup 05/09/03 24/09/03 98.03 ✓ 99.07481 S. bareilly 05/09/03 24/09/03 98.23 ✓ 99.81482 S. alachua 05/09/03 24/09/03 98.02 ✓ 99.85483 S. albany Fail Fail484 S. adelaide Fail Fail485 S. emek 25/09/03 20/11/03 82.81 ✓ 90.27486 S. abony 25/09/03 20/11/03 75.02 X 89.25487 S. isangi 25/09/03 20/11/03 65.13 X 90.23488 S. florida 25/09/03 20/11/03 64.61 ✓ 88.59489 S. agona 25/09/03 05/12/03 69.67 ✓ 82.63490 S. ajioba 25/09/03 05/12/03 58.58 X 81.55

Fail: Isolate was not typable despite several repetitions.

CSG 15 (Rev. 6/02) 11

Thirty-nine from 91 strains were clustering together on a dendrogram that contained all repeated strains. The dendrogram of these 39 strains is shown in Figure 1.

Figure 1. Dendrogram of 39 minor animal derived S. enterica subsp. enterica serovar isolates that clustered together when a panel of 91 strains was typed by f-AFLP on an independent occasion.

Pearson correlation [0.0%-100.0%]aflp2

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vinorhrady

eimsbuettel

tel-el-kebir

waycross

arechararleta

bredney

rubislaw

eastbourne

durban

cerro

duesseldorf

agama

caracus

fresno

poona

tel-aviv

indiana

hindmarsh

kentucky

dublin

anatum

coeln

chailey

durham

pomona

uganda

stanleyville

blockley

bareilly

sorenga

wandsworth

saint-paul

stanley

emek

tees

marina

kedougou

florida

wangata

409

458

401

411

477

479

415

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485

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416

When these 39 minor serovars were compared with corresponding isolates from human, food and feed sources that were analysed during an earlier project year, none of the strains grouped together with the corresponding serovar from another source. The dendrogram of the minor serovars from human, food and feed sources is shown in Figure 2.

Figure 2. Dendrogram of 39 minor animal derived S. enterica subsp. enterica serovar isolates from human, food and feed sources that were typed by f-AFLP a year prior to the present work.

Serovars from isolates derived from animal sources were better discriminated than the corresponding serovars from human, food and feed sources. Figure 1 shows that most serovars fall within 70–90% similarity whereby this range is narrower on Figure 2 and a higher number of strains cluster closer to 80% similarity.

A selection of 22 major serovars from animal origin was further typed by f-AFLP and repeated on an independent occasion. Table 3 shows the similarity of the repeated typing patterns of the strains and the corresponding internal standards. While the similarities are higher on an average than those observed with some of the minor serovars, on a combined dendrogram none of the 22 major serovars clustered with its replicate counterpart.

CSG 15 (1/00) 13


100

9080706050403020

aflp2

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wangata

vinohrady

chailey

uganda

duesseldorph

tel-el-kebir

anatum

amager

hindmarsh

indiana

sorenga

fresno

kedougou

tel-aviv

waycross

bareilly

saint-paul

rubislaw

dublin

durham

arecharalet

poona

cerro

pomona

durban

bredney

caracus

eastbourne

blockley

kentucky

emek

stanley

wandworth

stanleyville

coeln

tees

florida

eimsbuettel

marina

235

238

223

228

222

230

206

208

200

128

287

302

264

215

296

161

129

280

202

189

218

306

190

137

205

194

253

203

133

162

174

167

295

217

219

289

231

198

139

Table 3. Similarity in percentage between replicate analysis of animal derived major Salmonella enterica subsp. enterica serovars and the internal sample standards for f-AFLP analysis.

Strain number Major serovar Similarity between similar strains (%)

Similarity between internal standards (%)

491 S. typhimurium 68.5 88.26492 S. typhimurium 77.74 88.51493 S. typhimurium 82.56 91.03494 S. typhimurium 73.82 88.05495 S. typhimurium 78.5 90.64496 S. typhimurium 71.95 88.01497 S. typhimurium 77.11 88.42498 S. typhimurium 82.58 88.07499 S. typhimurium 82.94 91.67400 S. typhimurium 80.55 87.71501 S. hadar 79.81 89.49502 S. hadar 75.91 89.05503 S. hadar 63.7 88.17504 S. hadar 56.91 88.41505 S. hadar 62.81 87.78506 S. hadar 62.94 88.08507 S. hadar 69.19 87.83508 S. virchow 61.12 88.34509 S. virchow 77.69 84.36510 S. virchow 79.86 85.05511 S. virchow 81.87 86.26512 S. virchow 78.33 87.61

It was observed that the internal standards from the majority of samples analysed in the final project year displayed good reproducibility. However, comparisons made between the internal standards from the year before and the present year were around 75% related. This was due to interim equipment relocation within the laboratory. This needs to be kept in mind when unique, reproducible fingerprints for strain identification need to be achieved as a potential source of difficulties for the reliability of the f-AFLP technique.

2.2.2. Comparison of f-AFLP dendrograms obtained from strains after isolation from fresh and frozen minced beef In order to investigate potential effects of the food matrix on the dendrogram patterns of similar Salmonella strains, a blind study was carried out. This was achieved by blind selection of a panel of 30 Salmonella animal isolates taken from the extended strain list of 113 Salmonella animal isolates. Panel selection was made by a member of staff not associated with the project. Each strain was grown in broth culture which was then aliquoted into three samples. One sample was used in to inoculate fresh meat, another frozen minced meat and the reminder subjected to DNA extraction and subsequent f-AFLP analysis. The Salmonella strains from both the meat samples were isolated following the BS Standard method (2002). Following isolation and growth in medium, DNA was extracted and subjected to f-AFLP analysis. The patterns of the three independent sets of data were compared using the samples and their corresponding internal standards. The results are displayed in Figures 3–5. Figure 6 displays a dendrogram of internal standards from samples corresponding to the analysis of frozen meat isolates. Dendrograms for the internal standards of the other matrices are not shown. Generally, the internal standards for all three matrices gave similarities of 94–99.8%.

CSG 15 (1/00) 14

Figure 3. Dendrogram of 30 Salmonella enterica subsp. enterica isolates from animal origin used for f-AFLP analysis after growth in medium.

CSG 15 (1/00) 15


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Figure 4 Dendrogram of 30 Salmonella enterica subsp. enterica isolates from animal origin used for f-AFLP analysis after isolation from fresh minced beef.

CSG 15 (1/00) 16


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Figure 5. Dendrogram of 30 Salmonella enterica subsp. enterica isolates from animal origin used for f-AFLP analysis after isolation from frozen minced beef.

CSG 15 (1/00) 17


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aflp2

26B

29B

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Figure 6. Dendrogram of internal standards of f-AFLP samples obtained after isolation of 30 Salmonella enterica subsp. enterica isolates from animal origin from frozen meat.

The similarity of the three origins of the isolates (broth, fresh or frozen meat) are displayed in Table 4.

CSG 15 (1/00) 18


100

9998979695949392919089

aflp2

ROX 1B

ROX 3B

ROX 11B

ROX 4B

ROX 5B

ROX 8B

ROX 2B

ROX 9B

ROX 12B

ROX 25B

ROX 30B

ROX 26B

ROX 29B

ROX 18B

ROX 23B

ROX 17B

ROX 15B

ROX 16B

ROX 24B

ROX 28B

ROX 20B

ROX 22B

ROX 21B

ROX 19B

ROX 13B

ROX 14B

ROX 6B

ROX 7B

ROX 10B

ROX 27B

Table 4. Similarities in percent between f-AFLP fingerprints directly from broth compared with the same isolate recovered from fresh or frozen minced beef.

Unknown Sample

Broth + Meat A Broth + Meat B Meat A + Meat B

1 89.1 62.8 67.02 82.2 63.3 58.23 87.4 70.4 66.34 77.9 67.7 65.65 87.1 64.2 65.86 86.2 80.2 67.47 88.9 62.5 61.38 83.9 54.0 64.69 89.6 66.4 59.4

10 97.3 82.6 81.411 88.0 73.3 69.012 85.6 78.8 64.913 90.4 72.5 56.914 89.0 67.0 52.915 90.9 67.8 73.416 89.7 65.9 68.517 91.6 71.1 73.918 90.0 66.9 69.219 72.1 75.5 61.420 69.0 78.2 62.321 78.5 69.5 86.022 64.4 77.4 58.023 66.5 85.3 60.124 44.7 81.1 57.925 62.1 90.3 61.426 67.1 91.2 66.527 55.0 60.2 61.828 60.7 80.5 67.629 64.6 81.5 65.030 64.1 88.4 63.9

2.2.3. Identification of 30 unknown S. enterica subsp. enterica isolates by comparison with a database of f-AFLP dendrograms with 113 strains of animal originEach f-AFLP profiles from the blindly selected panel of 30 Salmonella isolates were compared individually against the complete database of f-AFLP patterns from which they were selected. Both a targeted and direct comparison approach was undertaken to identify unknown isolates and to investigate the potential reliability of the technique for strain identification in an outbreak situation. Table 5 shows the deduced identification from the available information, and the actual identity of each isolate. Twenty-three of the 30 isolates were identified correctly. Seven of the 23 correctly identified isolates had a second option. Seven serovars from the 30 unknown isolates were identified incorrectly.

CSG 15 (1/00) 19

Table 5. Identification of 30 unknown S. enterica subsp. enterica isolates.

Unknown sample

Serovar Prediction Strain predicted Samples used for

comparison*

Similarity of samples (%)

Correct identification

1 virchow 512, 510 1, 510 91.6 5122 virchow 509 2, 509 90.8 5093 hadar 507 3A, 507 73.8 5064 hadar 501 4, 501b 86.6 5015 typhimurium 497 5, 497b 93.8 4976 typhimurium 499 6A, 499b 89.0 4947 ajioba 490 7, 490 83.9 4908 abony 486 8A, 486b 92.3 4869 alachua 482 9, 482b 70.1 482

10 arizonae 478 10A, 478 70.4 47811 bovis morbificans 474 11A, 474b 74.5 47412 grumpensis 470 12, 470 85.4 47013 corvallis 466 13A, 466 86.9 46614 poona 413 14A, 413b 70.0 S. cerro 46215 guiena 453 15, 453b 72.6 S. eimsbuttel 45816 richmond, canstatt 417, 461 16A, 461 77.3 S. kentucky 45417 amager 450 17B, 450b 75.3 45018 emek 485 18A, 485b 85.4 S. haardt 44619 napoli 442 19A, 442 74.3 44220 agama, munster 456, 438 20, 456b 74.5 43821 manhatten, virchow 434, 511 21B, 511 77.6 43422 virchow 509 22, 509 71.8 S. worthington 43023 zanzibar 426 23B, 426 79.9 42624 virchow, emek 509, 485 24, 509b 86.9 S. tees 42125 tennessee 404 25B, 404 81.1 S. richmond 41726 poona 413 26B, 413b 79.3 41327 vinorhady 409 27B, 409b 79.4 40928 ruiru, minnesota 405, 402 28, 402 74.9 40529 minnestoa 402 29, 402 71.1 40230 weltereden, guiena 400, 453 30B, 400 66.7 400

*A: isolate obtained from fresh meat, B: isolate obtained from frozen meat

We have been able to correctly identify 53% and a further 23% with a second option from a set of 30 unknown strains based on investigations done during the last project year. In Figure 7 a selection of examples is shown of dendrograms that were enabling the identification of the unknown in addition to a direct comparison of similarities between strains using the software.

CSG 15 (1/00) 20

Figure 7. Dendrograms that show the identification of unknown S. enterica subsp. enterica animal isolates No. 1, 2, 3, 4 and 5 by comparison with known strains from a database of f-AFLP fingerprints.

CSG 15 (1/00) 21


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3. Summary of results obtained in the prior project phase with PCR based methods, Pulsed-field Gel Electrophoresis (PFGE), Restriction Fragment Length Polymorphism (RFLP) and capillary electrophoresis

3.1. RAPD, ERIC- and REP PCR

It was found that RAPD-PCR amplification produced between 6 and 20 distinct DNA bands in the 1000–3500 bp range for Salmonella spp. Amplification bands were clearly resolved using agarose gel electrophoresis, producing profiles of sufficient quality for BioNumerics analysis. Analysis of RAPD-PCR typing of minor serovars, Salmonella indiana, S. schwarzengrund and S. derby indicated that this method enabled some serovar discrimination. BioNumerics analysis of RAPD-PCR typing for the major serovar S. typhimurium, was carried out to determine whether RAPD typing could be used to discriminate within the serovar. There was some discrimination at the 85% level whereas most strains fall within 90% similarity.REP-PCR amplification generally produced profiles containing 10-25 distinct bands. Profiles for Salmonella strains were separated by agarose gel electrophoresis, enabling easy profile analysis using BioNumerics.Representative profiles were obtained for the minor serovars S. derby and S. montevideo. The serovars were separated into distinct groups with 55% similarity. Within the S. montevideo serovar discrimination at the 85% level was observed. Two of eleven strains of S. derby were distinguished with 50 and 60% similarity whereas the other were clustering at around 80%. Very little discrimination was observed within the serovar of S. indiana and higher variability within S. schwarzengrund. ERIC PCR typing of Salmonella spp. produced reproducible profiles containing 10-20 bands of between 300–3500 bp. Profiles generated for strains belonging to the major serovars S. enteritidis and S. typhimurium showed little intra-serovar discrimination. BioNumerics analysis of S. derby, S. schwarzengrund and S. indiana showed equally little within serovar discrimination. All three PCR based techniques would be mainly suitable for a discrimination between serovars and to a lesser extent within serovars.

3.2. PFGE

PFGE is a suitable technique to separate DNA fragments of high molecular weight. Suitably sized DNA fragments derived from Salmonella were generated using the rare cutting restriction fragment XbaI. BioNumerics analysis of three minor serovars, S. derby, S. schwarzengrund and S. indiana showed inter serovar discrimination of 70–75%. Within serovars differentiation of about 88% was observed. PFGE showed better intra-serovar discrimination of the major serovar S. typhimurium of around 60–70%. Very little differentiation was observed between phage type DT104 isolates.

3.3 RFLP

A small panel of restriction endonucleases were evaluated on the minor serovars S. thompson and S. stanley for their effectiveness in RFLP typing. A number of rare cutting restriction endonucleases were examined alongside EcoR1. Low molecular weight bands were not detected by ethidium bromide staining on genomic extracts digested with either SfiI, SpeI or SwaI. In contrast, profiles obtained using BlnI, EcoRI and SnaBI gave numerous bands in the 1000-7000bp region. The rare cutting restriction enzyme SnaBI was selected for RFLP analysis of the S. enteritidis, S. virchow, S. hadar and S. typhimurium serovars.Genomic digestion using SnaBI was carried out on sixteen S. enteritidis strains. DNA fragments were separated by agarose gel electrophoresis and then analysed. The RFLP profiles were found to be complex and poorly resolved. Analysis of the RFLP profiles using BioNumerics software was carried out, but it was noted that the software could not discriminate between the worst of the poorly resolved bands. Of the sixteen strains analysed, fifteen were of sufficient quality for BioNumerics analysis and dendrogram comparison. There were four main clades at the 93% level, with one strain clustering at 90%. Such similarity signified that the S. enteritidis strains tested could not be differentiated using this technique.

3.4. Capillary electrophoresis

The capillary gel electrophoresis technique was optimised using a 100bp DNA ladder (Promega Life Sciences) . Use of a coated capillary with an internal diameter of 75m, heated to 40oC provided good resolution of DNA fragments up to 1.5kb in 30 minutes. The presence of salts in both PCR and RFLP samples caused preferential salt injection onto the capillary, and shallowing of DNA peaks. Samples were therefore dialysed against sterile Milli-Q ™ water (Fisher Scientific, Loughborough, UK) for 1 hour across a treated cellulose membrane (Sigma, Poole, UK). Addition of an internal standard (Bromophenol blue, 0.5mg ml-1) enabled easy tracking of DNA peaks throughout a run. It was found

CSG 15 (1/00) 23

that the detection limit of the Biofocus 3000 capillary instrument, (Bio-Rad, Hemel Hempstead, UK) was 10ng. To compare, the detection of DNA in ethidium bromide stained gels is reported to be around 1ng.Due to the variation experienced in both the external and internal standard migration times, it was necessary to establish two parameters to ensure reliable data analysis. The first parameter ensured that only batches of samples with an external standard with correlation coefficients of 0.99 or greater were analysed. The R-value in this instance was defined as: The correlation between the true migration time of each component in the standard to the line of best fit of migration times against size of DNA fragment. Following R-value analysis of standards, 59% of all sample capillary traces were analysed further. The second parameter ensured that samples were only analysed if consistency in migration times for the whole batch could be demonstrated. The internal standard migration times were compared with the mean migration time for the data set, and percentages both above and below the mean value were calculated. Further analysis was carried out when all of the internal standard migration times of a given data set fell within ± 5% of the mean internal standard migration time . Following internal standard analysis, 48% of all sample capillary traces were analysed further.Capillary analysis of RFLP fragments generated from seventeen S. typhimurium strains, three S. virchow strains and twelve S. hadar strains was carried out. Peaks of DNA and the internal standard were detected between 10 and 30 minutes. The genomic digests of the Salmonella strains tested yielded between 2 and 4 detectable DNA fragments. Fragments were found to have similar migration times, making differentiation of individual serovars difficult. BioNumerics analysis and dendrogram comparison of the RFLP data indicated that there were five clades at the 70% level, each consisting of a mix of the serovars tested.Separation of ERIC-PCR fragments using capillary electrophoresis enabled detection of DNA fragments and the internal standard between 10-30 minutes after sample injection. DNA fragments, sized between 100bp and 700bp were separated with good resolution, and fragments of 700bp to 1500bp with peak widening. Due to the variation experienced in the capillary data, it was only possible to analyse 37% of traces produced. In general, the ERIC-PCR technique yielded between 2 and 4 detectable DNA fragments in the 100bp to 1500bp region. By comparison, agarose gel separations of duplicate samples enabled detection of between 8 and 12 DNA fragments. Comparisons made between capillary electrophoresis traces, and agarose gel fingerprints indicated that the Biofocus 300 capillary electrophoresis instrument restricted DNA detection to concentrated DNA fragments only. BioNumerics analysis carried out on capillary separated ERIC-PCR amplification products from the major serovars, S. enteritidis, S. typhimurium, S. virchow and S. hadar as well as some strains belonging to the minor serovars, indicated that strains from the same serovar were not clustering together. Five main clades consisting of mixed serovar groups were separated at the 70% level, with several outliers. This finding was contradictory to BioNumerics analysis of the ERIC-PCR DNA fragments separated by agarose gel electrophoresis, in which inter-serovar discrimination was displayed. To determine whether intra-serovar discrimination was achieved using capillary electrophoresis separation of ERIC-PCR DNA fragments, dendrograms were prepared from both the S. enteritidis and S. typhimurium data. These dendrograms indicated that intra-serovar discrimination was not achieved at the 70% level or better. This was unsurprising due to lack of serovar discrimination and lack of analysable DNA peaks. Separation of f-AFLP fragments using capillary electrophoresis enabled detection of DNA fragments and the internal standard between 10 and 30 minutes after sample injection. DNA fragments sized between 100bp and 700bp were separated with good resolution, and fragments of 700bp to 1500bp with peak widening. Fragments of DNA of greater than 500bp were not detectable using the ABI PRISM 377 (Applied Biosystems) electrophoretic method, as the guidelines for f-AFLP analysis advised by Applied Biosystems were followed in this project. Due to the variation in the capillary data quality only 56% of the capillary traces produced could be analysed. Depending on the Salmonella strain typed and the DNA concentration, between three and eight f-AFLP fragments were detected by capillary electrophoresis. This was considerably less than the 40 to 80 f-AFLP fragments detected using ABI PRISM 377 separation. Dendrogram analysis of the capillary separated f-AFLP data showed that serovar discrimination was not possible with this combination of techniques.

4. Discussion

The five most commonly occurring Salmonella serotypes in humans reported to the Public Health Laboratory Service in England and Wales during 2000 were S. enteritidis, S. typhimurium, S. hadar, S. virchow and S. infantis. Although S. enteritidis and S. typhimurium accounted for more than 75 per cent of the cases, these two serotypes have broad ranges of infecting a wide range of birds and mammals. In the case of live stock, the five most common serotypes reported to the Veterinary Laboratories Agency during the same period were S. dublin, S. typhimurium, S. senftenberg, S. give and S. montevideo, with the first two accounting for more than 75 per cent of the incidences (Anonymous, 2000).In our study, we analysed a representative number of strains isolated along the food chain covering the way from farm via folk to the consumer. The main emphasis was in the final project year on the f-AFLP technique and its potential to identify unambiguously Salmonella isolates in an outbreak situation. The discrimination within the major serovars from animal origin was around 90% for the majority of strains. This indicated some lack of inter serovar discrimination. Similar results have been obtained previously for the major serovars from human, food and feed origin. For

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representatives of the minor serovars there was a slightly better discrimination for isolates derived from animal sources than those from human, food and feed origin. The main concern that was observed with the technique was reproducibility. There appears to be a need to standardise the methodology as data from our laboratory was variable and a relocation of laboratory equipment had a significant impact on the comparability of data. In our investigations an internal standard was used to allow to compare fingerprint pattern directly from different runs and to compare new patterns with previously stored fingerprints. This approach has been recommended in the literature previously (Lindstedt et al., 2000). Our data indicated that a replicate analysis is not sufficient and triplicate repeats are recommended in line with Fry et al. (2002). On the other hand, we were able to correctly identify 53% and a further 23% with a second option from 30 unknown isolates based on comparison with prior analysis data. This indicates the possible potential of f-AFLP when optimised and standardised to be successfully applied for outbreak recognition.Pulsed-field electrophoresis (PFGE) is currently the method of choice for typing Salmonella strains. PFGE has good discriminatory power and has proven highly useful and reliable in outbreak situations (Ridley et al., 1998). In our investigation the discriminatory power of f-AFLP and PFGE for the range of strains investigated were comparable. This observation was supported by other studies that compared the two method with S. enterica subsp. enterica serovars (Lindstedt et al., 2000, Tamada et al., 2001). An investigation of the S. enterica serovar enteritidis phage type 4 clone complex has demonstrated a higher discriminatory power of f-AFLP by around 50% (Desai et al., 2001). PFGE showed in our investigation a higher degree of discrimination amongst S. typhimurium than f-AFLP. A number of strains were similar at the 70% level. However, representatives of the phage type DT104 were not differentiated and showed similarity at 100%. PFGE promoted good discrimination within minor serovars of S. bredeney, S. schwarzengrund, S. heidelberg and S. agona, S. stanley, S. indiana, S. abony, S. chester, S. brandenburg, S. san-diego, S. stanleyville, S. reading, S. derby. In most sets of minor serovars some strains were not separated from each other. This indicated that PFGE does not identify all Salmonella isolates unambiguously.Randomly amplified polymorphic DNA (RAPD) analysis has been successfully applied to typing of avian Salmonella enterica subsp. enterica isolates (Chansiripornchai et al., 2000). Our investigation revealed that the three PCR based techniques, RAPD, repetitive extragenic palindromic sequences (REP) and enterobacterial repetitive intergenic consensus sequences (ERIC) PCR, discriminated at a serovar level and displayed a lack of discrimination within serovars at a strain level. This observation is consistent with reports in the literature (Kerouanton et al., 1996; Beyer et al., 1998). The highest discriminatory power of the three techniques was observed in our investigation for ERIC PCR.Investigation concerning RFLP revealed that the method protocol applied did not reveal advantages in the discrimination of isolates when compared to PFGE and the PCR based techniques. Using the protocols and equipment described in this study, it was not feasible to couple capillary electrophoresis separation with endonuclease digested genomic DNA to improve discrimination of different strains of Salmonella. The successful application of capillary electrophoresis to separation of PCR fragments has been described for f-AFLP (Lindstedt et al., 2000, Desai et al., 2001). Our investigations revealed difficulties with the capillary equipment available and its sensitivity and reproducibility. The capillary data obtained for f-AFLP indicated that there were f-AFLP fragments of greater than 500bp. Extending the calibration range of the ABI PRISM 377 to greater than 500bp may enable further differentiation of the Salmonella strains.In conclusion, we found that not all strains were discriminated when relying on only one method. Each method has its own characteristic advantages and limitations. This has been described and concluded from other investigations. An influence of a serotype on the isolating strategy was described. The authors concluded that a single method cannot be relied upon for discriminating between strains and that a combination of methods would allow further discrimination (Liebana et al., 2001, Liebana et al., 2002). Our investigation revealed that PFGE and f-AFLP are the most powerful and promising techniques for differentiation to strain level. Results from f-AFLP indicated a need to standardise and carefully interpret data by relying on internal standards and at least triplicate analysis.

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