Design and evaluation of PCR primers which differentiate Escherichia coli O157:H7 and related serotypes


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William C. Rice, USDA, ARS, Conservation and Production Research Laboratory, PO Drawer 10, 2300 Experiment Station Road, Bushland, TX 79012-0010, USA.


Aims:  To develop methods to differentiate Escherichia coli O157:H7 and related serotypes by the use of amplicon length polymorphism (ALP) analysis based on identifying DNA sequence deletions within highly homologous regions of three sequenced E. coli strains.

Methods and Results:  Potential primer locations along the ancestral genomic backbone were identified and evaluated against three sequenced genomes and then applied to a reference set of pathogenic E. coli strains. All 16 primer combinations generated the expected diagnostic fragments as predicted for the E. coli K12 MG1655, O157:H7 EDL933, and O157:H7B Sakai genomes.

Conclusions:  This study defines a collection of primers distributed along the length of the E. coli genome that were applied to ALP analysis methods to successfully differentiate between serotypes of E. coli O157:H7 and other E. coli serotypes.

Significance and Impact of the Study:  ALP-PCR analysis method was validated as an independent method of classification when compared with that of rep-PCR. The principles underlying ALP analysis can be readily applied for the detection and differentiation of other closely related microbial species because of the abundance of complete DNA sequence data for a large number of microbial genomes.


Escherichia coli O157:H7 is a major food-borne infectious pathogen and, because of its worldwide distribution, is a serious threat to public health systems. Escherichia coli O157:H7 was first recognized following two outbreaks in Michigan and Oregon in 1982 (Riley et al. 1983) and can cause diarrhoea, hemorrhagic colitis, and haemolytic uremic syndrome. In the United States, approximately 75 000 cases of O157:H7 infections are now estimated to occur annually (Mead et al. 1999). Important virulence attributes that have been identified are shiga toxin production (Konowalchuk et al. 1997), characteristic attaching and effacing (A/E) lesions and intimin protein production encoded by the eae gene (Knutton 1995; Whittam 1998). However, several lines of evidence underscore the fact that other unknown virulence factors may be expressed by E. coli O157:H7. Strains of E. coli that are eae negative are still capable of colonizing the intestinal epithelium (Su and Brandt 1995; Tzpori et al. 1995) and other strains of E. coli that show different levels of shiga toxin production have the same clinical manifestation (Paton et al. 1999).

In order to better understand the pathogenesis and evolution of E. coli O157:H7 and to develop better methods of identification, several groups have completed the DNA sequence determination of two genomes of E. coli O157:H7; isolates O157:H7 EDL933 (Perna et al. 2001) and O157:H7B Sakai (Hayashi et al. 2001). The Sakai strain was implicated in a major enterohaemorrhagic E. coli O157:H7 outbreak in Japan (Watanabe et al. 1996). A 4·1 Mb ancestral genomic backbone was implicated between the DNA sequence of the two O157:H7 genomes and that of the previously sequenced common laboratory strain of E. coli K12 MG1655 (Blattner et al. 1997). Evidence for a common E. coli genomic backbone had already been suggested by multilocus sequencing of seven housekeeping genes of E. coli O157:H7 (Reid et al. 2000). Significant lateral gene flow was observed between the genomes and attributed in part to prophages. Approximately 800 kb of DNA is unique to the O157:H7 serotypes and thus contains the gene function(s) that are responsible for severe infections caused by E. coli O157:H7 serotypes. These include putative virulence factors, alternative metabolic capacities, prophages and other new functions.

There are many methods (reviewed, Olive and Bean 1999) each with their respective advantages and disadvantages that have been developed to type and subtype various microbial organisms. The advantages of the sensitivity and speed of polymerase chain reaction (PCR) based approaches have been recognized along with some of the attendant draw backs. DNA sequence determination and analysis is often considered along with pulse field gel electrophoresis as a ‘gold standard’ for microbial genome identification and typing; however, these approaches require the greatest amount of time and expense.

Herein, the advantages of the wealth of DNA sequence knowledge regarding the E. coli O157:H7 and K12 genomes and the power of PCR to rapidly detect and differentiate various E. coli O157:H7 genomes and other related ‘O’ serotypes are combined. A number of papers have been published to detect and/or differentiate between various E. coli genomes based on the O antigen coding locus. Some of these E. coli serogroups are O15 (Beutin et al. 2005), O26 and O111 (Louie et al. 1998), O104 (Wang et al. 2001), O138 and O139 (Wang et al. 2005), O145 (Feng et al. 2005) and O111, O113, and O157 (Paton and Paton 1999). They are detected and/or differentiated using gel based methods, whereas real-time PCR assays have been developed for the analysis of E. coli serogroups O103 (Perelle et al. 2005) and O157 (Fortin et al. 2001). All the above-mentioned methods are targeted at specific genes within the O antigen gene locus and are limited in their ability to differentiate among all serogroups. Methods of amplicon length polymorphism (ALP, Ghareyazie et al. 1995) in rice genome analysis were developed based on identifying DNA sequence deletions within highly homologous regions. The suitability of the ALP method was evaluated using three sequenced E. coli strains. Potential primer locations along the ancestral genomic backbone were identified and evaluated against these three sequenced genomes and then applied to a reference set of pathogenic E. coli strains. Results obtained from ALP analysis were compared with those obtained by an established typing method such as repetitive extragenic palindromic-PCR (rep-PCR) based method (Versalovic et al. 1991) and these efforts are presented in this study.

Materials and methods

Bacterial isolates

The DECA set of E. coli strains (n = 75, when received) contains representative isolates of 15 common diarrheagenic clones (Table 1) based on electrophoretic types (ET). The ET classification provides a clonal framework for assessing the diversity of E. coli strains. The DECA set is comprised of 28 serotypes and was obtained along with the O157:H7 EDL933, and the O157:H7B Sakai strains from the National Food Safety and Toxicology Center at Michigan State University (2002) (East Lansing, MI, USA), while the E. coli K12 MG1655 strain was obtained from the E. coli Genetic Stock Center at Yale University (New Haven, CT, USA). Additional information regarding DECA strains may be obtained from the STEC centre (

Table 1.   DECA set of strains used in this study
CodeSerotypeEt classCodeSerotypeEt class
  1. na, Not available.

DEC6DO:H -nanaDEC14BO128:H21DECr6

DNA isolation

DNA was isolated using the PUREGENE DNA Isolation Kit (Gentra Systems, Minneapolis, MN, USA) according to manufacturer’s protocol for Gram-negative bacteria. DNA yield was determined using the Hoechst dye method (Cesarone et al. 1979) using a VersaFluor fluorometer according to manufacturer’s protocol (BioRad Laboratories, Hercules, CA, USA).

DNA homology analysis

Global alignment of E. coli strains K12 MG1655 (accession L48811), O157:H7 EDL933 (accession AE005174), and O157:H7B Sakai (accession BA000007) genomic DNA sequences was performed using Align Plus v4.1 (Sci-ed Software, Durham, NC, USA). Genomic DNA homology analysis was performed as two-way alignments of approximately 2 Mb blocks of DNA using the FastScan program set for maximum score. Initially the E. coli K12 MG1655 genome was aligned against O157:H7 EDL933 genome and the O157:H7 EDL933 was aligned against O157:H7B Sakai genome. In this way, major regions (≈100–600 kb) of high homology (≥97%) were identified. Three-way global alignments were then conducted using either the K12 MG1655 or the O157:H7 EDL933 genome as the reference genome dependent upon which two genomic regions shared the greatest homology. This method identified deletions within a genome (either the K12 or the two O157 genomes) such that it was possible to amplify a single unique PCR generated diagnostic fragment with respect to either the K12 or the two O157 genomes (two exceptions noted later).

Polymerase chain reaction

Primers were designed and selected using various programs within Primer Design ver. 4.2 (Sci-ed Software, Durham, NC, USA) against K12 MG1655 or O157:H7 EDL933 genomes. Criteria used for primer construction were: length (20 bp), %GC (50–60), Tm°C (55–80), 3′ dimers (<3), dimers-any (<7), stability (>2·0 kcals 5′vs. 3′), runs (<3), and repeats (<3). Primers that ranked high in these criteria, that were located within homologous regions flanking small deletions (<1500 bp), and were widely distributed within the E. coli genomes were then subjected to Primer Mix analysis (Primer Design v4.2 software) performed against some of the various complete microbial genomic DNA sequences deposited in GenBank. Primers successfully meeting the above cited criteria were selected for use in PCR analysis and used to generate computer derived amplicons for each genome. Primer sequences (5′ to 3′) along with their genomic locations and amplicon designations are listed in Table 2.

Table 2.   Primer sequences and amplicon designation used in this study
AmpliconPrimer*Primer sequence 5′–3′T-An†Predicted fragment (bp)
  1. *F forward primer, R reverse primer, number indicates location on K12 or O157 (O-) genome.

  2. †T-An annealing temperature.

  3. ‡Data not used in cluster analysis.

O-C‡O157-F596247gtcgctctcggtcagcacta570468777, 468

ALP-PCR reactions (25 μl) contained the following: 50 ng of template DNA, 1× reaction buffer (Gibco BRL, Grand Island, NY, USA), 1·5 mmol 1−1 MgCl2, 200 μmol 1−1 of each dNTP, 20 pmol of each primer, and 1 U of Platinum TaqI DNA polymerase (Gibco BRL). A BioRad iCycler thermocycler (BioRad Laboratories, Hercules, CA, USA) was used with a temperature profile of 2 min at 95°C, followed by 29 cycles of 30-s denaturation at 95°C, 30 s at the respective annealing temperature (Table 2), and 1-min extension at 72°C. The 29 cycles were followed by one cycle for 7·5 min at 72°C. Rep-PCR reactions conditions (Woods et al. 1992) were similar to ALP-PCR except the annealing reaction was performed at 44°C and 40 pmol of the following primers REP1R-I (5′-IIIICGICGICATCIGGC-3′) and REP2-I (5′-ICGICTTATCIGGCCTAC-3′) were used per reaction. Interspersed repetitive DNA sequence (BOX)-PCR was performed using the BoxA1R primer and BoxA1R PCR reaction conditions were identical to the rep-PCR conditions, except that an annealing reaction was performed at 50°C. Aliquots (5 μl, ALP-PCR; 12 μl, rep-PCR) from each reaction set were run on a 1·4% or 1·5% agarose gel depending on the size of the amplicon generated and stained with ethidium bromide (Sambrook et al. 1989). All PCR assays were repeated at least twice to verify the validity of the primer reaction sets.

DNA and data analysis

DNA gel images were captured and analysed by using a computerized video image analysis system (Kodak Digital Science Image Station Model 440CF, Eastman Kodak, Rochester, NY, USA) and exported as TIFF files. DNA molecular weights of observed fragments were determined using image analysis software v3.5.4 (Kodak Digital Science, Rochester, NY, USA). The pGEM and 100-bp DNA Ladder markers (Promega, Madison, WI, USA) and the high-throughput ladders I and II (Bioline, Randolph, MA, USA) were used as size standards. Banding patterns for each isolate were recorded as a categorical code: i.e. the base pair value present in Table 2 for a K12 MG1655 or for an O157:H7/O157:H7B generated amplicon was used. Missing bands were coded as 0 and novel bands were co-coded as the molecular weight value determined by analysis of agarose gel electrophoresis.

Analysis of the categorical scores from the ALP-PCR reactions was performed using Bionumerics software program version 5.0 (Applied Maths, Austin, TX, USA). A similarity matrix was calculated using the Multi-state coefficient categorical (based on all primer sets in Table 2 except O-C). Analysis of the composite dataset based on rep-PCR assays employing primer sets BoxA1R and REP1R-I_ REP2-I PCR DNA gel images was performed using various programs within the Bionumerics software program version 4.0 (Applied Maths, Austin, TX, USA). Identical molecular weight standards were included in each gel to allow for normalization of gel images for valid between-gel comparisons of DNA fingerprints. Similarity matrices of densitometric curves from the rep-PCR profiles were calculated using the Dice coefficient. Cluster analysis of the similarity matrices were performed by an unweighted pair group method with arithmetic mean (UPGMA) algorithm (Sneath and Sokol 1973) (data averaged from both experiments). The correlation was expressed as per cent similarity. Two tests (Pearson correlation and Kendall’s Tau) were conducted to assess the degree of congruence between the ALP and rep-PCR assay methods.


Global alignment of the E. coli K12 MG1655, O157:H7 EDL933 and O157:H7B Sakai genomic DNA identified regions of high homology shared by all three genomes that were interspersed with regions of low homology, deletions or both. Computer generated amplicons respective to each primer-genome set were globally aligned to indicate the DNA homology present at each genomic location (e.g. amplicons F and G, Fig. 1). Sixteen primer combinations (Table 2) were selected for their ability to detect and differentiate E. coli K12 MG1655, O157:H7 EDL933 and O157:H7B Sakai genomes and were then evaluated against various E. coli serotypes within the DECA strain set. These primers span a 2-Mb region surrounding the origin of replication and a 1-Mb region within the middle of the E. coli genomes. Results of ‘in silico’ Primer Mix analysis against selected Gram-negative and Gram-positive microbial genomes indicate that each primer combination is specific only to E. coli K12 MG1655, O157:H7 EDL933, and O157:H7B Sakai genomes (Table 3). Either one or the other primer or both would fail to bind at respective annealing temperatures, thus no amplifiable product would be produced.

Figure 1.

 (a, b) Homologous regions for Escherichia coli K12 MG1655, O157:H7 EDL933 and O157:H7B Sakai genomic amplicons generated by primer sets F and G respectively.

Table 3.   Results of primer set design analysis with other microbial genomes
GenomeAccession no.Predicted bands
Salmonella enterica serovar TyphiAL513382None
Salmonella typhimurium LT2AE006468None
Listeria monocytogenes EGDNC-003210None
Listeria innocua Clip11262AL592022None
Pasteurella multocida PM70AE004439None
Campylobacter jejuniAL111168None
Pseudomonas aeruginosa PA01AE004091None
Methanobacterium thermoautotrophicum delta HNC-000916None
Bacillus subtilisNC-000964None
Bacillus haloduransNC-002570None

All 16 primer combinations generated the expected diagnostic fragments as predicted for the E. coli K12 MG1655, O157:H7 EDL933, and O157:H7B Sakai genomes (Figs 2a,b and 4b). As noted earlier, primer sets O-C and O-E generated a different fragment for each microbial genome. Primer set O-C (Fig. 2a, lanes 24, 25, and 26) identified a region of repeated DNA that contained two copies of the forward primer resulting in generation of two amplicons. Several primer sets (not shown in Table 2) identified genomic regions containing multiple copies of one or more of the primers that could possibly generate six to ten amplicons within a single genomic location. Thus, a specific K12 or O157:H7/O157:H7B genomic backbone can be correlated to a genomic region based on the use of these primer sets.

Figure 2.

 (a) Amplicons generated by primer sets A, B, C, D, F, OB-I, and O-C for Escherichia coli genomes K12 MB 1655 (K), O157:H7 EDL933 (E), and O157:H7B Sakai (S) respectively. (b) Amplicons generated by primer sets E, G, L, O, R, OB-A, OB-F and OB-O for E. coli genomes K12 MB 1655 (K), O157:H7 EDL933 (E), and O157:H7B Sakai (S) respectively.

Figure 4.

 Amplicons generated by primer sets O-C (a) and O-E (b) respectively for DECA strains. Lanes: M, 100 bp ladder; 1, DEC5A; 2, DEC5B; 3, DEC5C; 4, DEC5D; 5, DEC5E; 6, K12 MB 1655; 7, O157:H7 EDL933; 8, O157:H7B Sakai; M, 100 bp ladder.

Evidence for the genomic plasticity of the O serotypes in the DECA strain set is indicated by the patterns of bands observed with various primer combinations (e.g. primer sets A and G, Fig. 3a,b). Eight unique bands (i.e., not predicted) were observed in a number of strains (range 1–19) with respect to six of the primer sets utilized (e.g. primer set A, Fig. 3a; Table 4). In addition, five of the primer sets failed to generate amplicons in a number of strains (range 1–36). The most likely explanation for strains that fail to amplify for a given primer set is that the genomic sequence of that strain for that site has undergone a mutation as all strains yield amplicons for the majority of primer sets evaluated. The 468-bp fragment amplified by primer set O-C was present only in serotypes O157:H7 and O55:H7 (Fig. 4a and data not shown). In all other O serotypes, the specific O157:H7B 777-bp fragment was observed. Primer set O-E is also capable of distinguishing among all three E. coli genomes, as O157:H7 and O157:H7B DNA generate differently sized amplicons, whereas K12 DNA does not yield a product (Table 2, Fig. 4b, lanes 6, 7, and 8). For the O-E primer set, the 624-bp fragment indicative of O157:H7 backbone was observed in 41 of the DECA strains, while in 9 of the DECA strains the 537 bp fragment or O157:H7B backbone was observed (Fig. 4a and data not shown). The rest of the strains failed to amplify, thus indicating a K12 backbone at this location or alternatively the insertion or transfer of a sequence from another E. coli strain. In all O157:H7 and O55:H7 serotypes in the DECA set of strains, the predicted O157:H7 and O157:H7B banding pattern was observed with all primer sets evaluated.

Figure 3.

 Amplicons generated by primer sets A (a) and G (b) for DECA strains. Lanes: M, 1, DEC1A; 2, DEC1B; 3, DEC2A; 4, DEC2B; 5, DEC3A; 6, DEC3B; 7, DEC4A; 8, DEC4B; 9, DEC5A; 10, DEC5B; 11, DEC6A; 12, DEC6B; 13, DEC7A;14, DEC7B; 15, DEC8A; 16, DEC8B; 17, DEC9A; 18, DEC9B; 19, DEC10A; 20, DEC10B; 21, DEC11A; 22, DEC11B;23, DEC12A;24, DEC12B; M.

Table 4.   Primer sets which amplify unique bands or no band is produce
AmpliconNo. strainsUnique bands (bp)Strains no band
OB-F91375, 73110
O-C151925, 900

Cluster analysis of the ALP generated banding patterns revealed three main clusters (similarity range of 63–76%) containing a number of distinct subclusters among the DECA set of strains (Fig. 5). One main cluster (similarity of 63·6%) consisted of two subclusters; the first subcluster (mean similarity of 74·5%) contained a total of 27 strains with the EDL933, Sakai, and the O157:H7, O55:H7, O55:H6 and O55:H5 serotypes present. In addition, note that the Sakai strain is differentiated from the EDL933 strain and other O157:H7 strains and that these strains of O157:H7 and O55:H7 serotypes are resolved into both subclusters. Four O157:H43/HNM serotypes formed an outlying nonsignificant cluster diverging with a mean similarity of 60%. The second subcluster of this group (mean similarity of 83%) was comprised mainly of O128, O111, O26 and O45 serotypes with EPEC2r6 as the dominant ET class. The other two dominant clusters were comprised of serotypes O128, O111, O45, O26, O52, O149 and O11 that formed a mixed distribution of subclusters within these main clusters (Fig. 5). The different O serotypes appear to be evenly distributed between these two main clusters and also appear to be influenced by their ET classification.

Figure 5.

 ALP-PCR dendrogram derived from cluster analysis of a similarity matrix calculated using the Dice coefficient. Cluster analysis was performed using the unweighted-pair group method, arithmetic average. Values are expressed as per cent similarity.

The composite rep-PCR dataset based on primer sets REP1R-I–REP2-I and BoxA1R revealed three main clusters with an observed range of similarities of 44–75% (Fig. 6). One main cluster contained all O157:H7 and O55:H7 serotypes with a mean similarity of 68% while another was comprised of all O55:H5 and O55:H6 serotypes with an overall similarity of 75%. The EDL933 and Sakai strains clustered together with an overall similarity of 87%. All other serotypes were distributed within the dominant main cluster with an overall similarity of 44%. Strains grouped within this dominant cluster appear to be influenced both by their serotype and ET class as was observed with the ALP dataset. Again O157:H43/HNM serotypes formed an outlying cluster (82% similarity).

Figure 6.

 Rep-PCR dendrogram derived from cluster analysis of a similarity matrix calculated using the Dice coefficient. Cluster analysis was performed using the unweighted-pair group method, arithmetic average. Values are expressed as per cent similarity.

An evaluation of the concordance observed between the experimental ALP method described here with a previously established method to measure genetic variation was determined. The Pearson correlation test revealed that 40% congruence was observed between the ALP and composite rep-PCR methods, whereas the Kendall’s Tau test indicated that there was a 28·73 ± 1·26% agreement between the methods.


This study defined a collection of primers distributed along the E. coli genome that can be used to both detect and differentiate between strains of E. coli O157:H7 and other E. coli serotypes. The 468 bp amplicon generated by primer set O-C was specific only to serotypes O157:H7 and O55:H7 while O-E primer set was capable of differentiating between K12, O157:H7 and O157:H7B. Application of a real-time PCR assay using a molecular beacon that targets the rfbE gene enables the detection of only O157:H7 serotype (Fortin et al. 2001) and can successfully differentiate O157:H7 from O55:H7. Additional primer sets employing gel based PCR assays have been developed to detect host specific eaeA gene homologs in E. coli serotypes O111:H8, O26:H11 and O157:H7 (Louie et al. 1998). These primers may prove useful in initial evaluations of large sets of suspect environmental isolates of E. coli O157:H7. The utility of primer sets described in this study are that they are capable of defining the extent of a K12 or an O157:H7 ancestral genomic backbone. This is based on the banding patterns that are observed with the various serotypes. Thus, a genetic relationship can be established for E. coli strains within the individual serotypes. In addition, the unique bands detected in some strains may be subjected to DNA sequence analysis to obtain evolutionary data and may also provide additional information that is useful for sub typing of E. coli serotypes.

Results obtained from the cluster analysis in this study are consistent with the proposal of E. coli O55:H7 as the ancestral parent of E. coli O157:H7 (Whittam et al. 1993). Additionally, cluster analysis results observed herein are consistent with the evolutionary results obtained by application of MLST of housekeeping genes that employed some of the strains that were used in this study (Reid et al. 2000). They also observed high similarity between O157:H7 and O55:H7 with O111 serotypes falling into another group of clustered strains and K12 in another distinct group. The fact that O157:H7, which is highly pathogenic to humans and O55:H7, is less so, suggests that genomic scale sequencing efforts should be directed at O55:H7. Complete DNA sequence analysis of O55:H7 genome should help to further define the evolution of O157:H7 and thus aid in the identification of additional genes involved in virulence. An evaluation of the overall concordance observed between ALP-PCR and rep-PCR methods suggests that there are different evolutionary pressures acting on the genomes of these various E. coli serotypes and that ALP method is useful in detecting some of these influences.

The combination of using genomic information (bioinformatics) with ALP-PCR analysis has resulted in a method to detect and differentiate various E. coli strains isolated from various sources (human, cow, calf, pig and hamburger) across many locations (over 25 countries and 15 states) into distinct genomic categories (clusters) independent of serotype classification, ET class, housekeeping genes and biochemical traits. Thus, a genetic index based on either K12 or O157 DNA sequences at specific genomic locations can be used to track lineages of various E. coli strains. This assessment cannot be made with other rep-PCR methods of analysis as the genomic locations of the repetitive DNA elements within a given strain are unknown. ALP- PCR analysis method was validated as an independent method of classification when compared with that of rep-PCR analysis method and along with other repetitive element PCR based assays may prove useful for high resolution differentiation of genetic relationships between very closely related strains.

Five rep-PCR DNA fingerprinting methods [rep-PCR, enterobacterial repetitive intergenic consensus (ERIC)-PCR, ERIC2-PCR, BOX-PCR and (GTG)5-PCR] have been compared against one another for their ability to differentiate faecal E. coli from humans, poultry and wild birds (Mohapatra et al. 2007). Cluster analysis and discriminant function analysis identified (GTG)5 as the best method available to differentiate amongst these various E. coli isolates. These five rep-PCR methods were subsequently evaluated in a bacterial source tracking (BST) study. The (GTG)5 method was shown to be the best method to differentiate amongst E. coli isolates from natural pond water. The suitability of ERIC-PCR for BST was evaluated against other methods that have traditionally been employed in various BST studies (Casarez et al. 2007). The three methods used for comparison against ERIC-PCR were pulsed-field electrophoresis (PFGE), automated ribotyping using HindIII, and Kirby-Bauer antibiotic resistance analysis (KB-ARA). It was concluded that construction of composite datasets, either two- or four-method datasets provided the highest rates of correct classification of isolates. ALP-PCR would appear to be a DNA fingerprinting method that is suitable for BST studies. Application of ALP-PCR (as it represents an independent method) with any of various rep-PCR assays or traditional BST methods mentioned above would contribute to improving rates of correct classification.

The principles underlying ALP-PCR method should be applicable to other micro-organism whose DNA sequence composition has been determined. The development of highly automated large-scale DNA sequencing machines has led to an explosion of microbial genome sequencing projects. Nearly 600 bacterial genomes and almost 50 Archaeal genomes have been sequenced (Liolios et al. 2007). Escherichia coli strains now represent 11 of these genomes with the addition of eight recently sequence E. coli isolates. These newly sequenced E. coli strains represent a future opportunity to realize the utility of the ALP-PCR approach.


The author would like to thank Mr Colby Carter for the preparation of media, bacterial DNA and reagents.