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Two novel, rapid assays were developed for speciation of bacterial mastitis pathogens using high-resolution melt analysis of 16S rDNA sequences. Independent DNA extractions were carried out on duplicate cultures of 13 major udder pathogen species and 13 coagulase-negative staphylococci (CNS). Real-time PCR amplification of 16S rRNA gene fragment, spanning the variable region V5 and V6, was performed with a resulting amplicon of 295bp. For the CNS species, a 16S rRNA gene fragment including the variable region V1 and V2 was selected with a resulting amplicon of 222 bp. Melt curves were generated, analysed and compared with the genetic differences in the respective target sequences of the different bacterial species. Of the 12 major pathogens, 10 had distinct melt curves. Complete discrimination was achieved in an additional step by creating heteroduplexes by adding known template to the reaction mix for the few overlapping species. All CNS species were reproducibly discriminated based on their distinct melt curves. The present study revealed that broad-range real-time PCR with HRMA can be used as a powerful, fast, low-cost tool for the differentiation of clinically important bacterial mastitis pathogens.
Mastitis, the most expensive disease of dairy cows, continues to be a persistent problem in the dairy industry (4). Improved techniques for the rapid and accurate detection and identification of the causative organism are critical to the judicious selection and timely use of the antibiotic of choice to control the inflammation of mammary gland (3). Accurate identification is often compromised when common bacterial species are presented with uncommon phenotypes, or when unusual species are encountered whose phenotypic profiles are not yet available in the database (36). An inherent weakness of phenotypic methods is that there is variability in expression of phenotypic characteristics by isolates belonging to the same species (2).
Coagulase-negative staphylococci (CNS) have become the predominant pathogens causing bovine mastitis in many countries (30, 32, 33, 38). CNS are the most common udder pathogens recovered from heifers, and a variety of CNS species have been recovered from teat skin, the streak canal and pre-calving udder secretion obtained from heifers (7, 29). Many schemes for the identification of CNS based on phenotypic characteristics have been developed (15), which require numerous media and are labour intensive. Even though, diagnostic laboratories utilize commercial test kits for phenotypic identification of CNS, these tests lack accuracy and their accompanying databases were mainly developed for human isolates (41, 43, 44, 47).
Because of the large and increasing diversity of microorganisms and the prevalence of organisms with rare, inconsistent or poorly defined phenotypic characteristics, conventional methods often cannot fully characterize bacterial isolates, and laboratories are increasingly relying on DNA-based sequencing for microorganism identification (47). Two PCR-based strategies have been developed for non-culture diagnosis of bacterial pathogens. The first approach targets species-specific genes for amplification, and the second uses broad-range PCR amplification of conserved bacterial DNA sequences, such as the 16S rRNA, 23S rRNA, and 16S-23S rRNA inter-space regions (1, 19, 20). For identification of CNS species, sequence data of housekeeping genes such asÂ rpoB,Â cpn60,Â dnaJÂ orÂ tufÂ can be used (16, 47). However, speciation based on sequencing following regular PCR is relatively costly and often requires days to get results when being outsourced. In clinical applications, real-time PCR for broad-range amplification of bacterial DNA offers additional benefits including minimal labor, rapid turnaround time, and a decreased risk of PCR carryover contamination as there is no need to separately analyze PCR products in the laboratory (28). Although probe-based assays and DNA sequencing of highly variable regions within the universal PCR amplicon have been used for phylogenetic analysis that in most cases leads to species-level identification, they are generally time-consuming and relatively expensive (14, 27). Recently, a high-resolution melt (HRMA) analysis incorporating the fluorescent dye EvaGreen has been used for detecting heterozygous and homozygous sequence variants for genotyping and variation scanning (9, 10, 18, 25, 35). This approach is a closed-tube technique that does not require fluorescently labeled probes or separation steps (45). In contrast to traditional melt-curve analysis, HRMA reliably detects single-base differences in homozygous and heterozygous sequences (48). Highly specific species identification of 100 clinically relevant biothreat bacterial agents using unique melt profiles generated from multiple hypervariable regions of the ubiquitous 16S rRNA gene has been reported earlier (46). Cheng et al. (12) combined the use of broad-range real-time PCR and high-resolution melt analysis for rapid detection and identification of clinically important bacteria. From these studies it was concluded that the HRMA can be a rapid and inexpensive technique with high sensitivity and specificity. Therefore, the aim of this study was to develop a HRMA based on the 16S rRNA gene that can rapidly identify and differentiate the most common bovine mastitis pathogens, including the CNS. The bacterial species targeted in this study are the common major and minor mastitis pathogens (34). Also included were mastitis pathogens which are not routinely identified by bacteriological culture due to their special growth requirements, such as the anaerobic Fusobacterium necrophorum, Bacteroides fragilis, Prevotella melaninogenica (17), the slow growing Corynebacterium bovis (42) and Arcanobacterium pyogenes (26), and the fastidious Mycoplasma bovis (8).
Materials and methods
Bacterial strains and isolates. The bacterial isolates employed in this study comprised of seven reference strains obtained from the American Type Culture Collection (ATCC), 14 directly obtained from the Canadian Bovine Mastitis Research Network (CBMRN) mastitis pathogens collection (37), and 5 isolated from milk samples originating from organic farms in Alberta (Table 1). The isolates obtained by culturing were subjected to further characterization and identification by morphological and biochemical reactions (5) and genotypically confirmed by sequencing of PCR amplicons based on the sequences of the16S rRNA gene (DNA core laboratory, University of Calgary). Of the 14 most frequently encountered mastitic staphylococcal spp. (39) obtained from CBMRN (excluding Staphylococcus aureus), 13 isolates were coagulase-negative and confirmed by rpoB gene sequencing at Faculty of Veterinary Medicine, Missouri, while the fourteenth isolate was coagulase-positive and confirmed by 16S rRNA gene sequencing.
Gene alignment. Reference sequences of the 16S rRNA gene were obtained from the Ribosomal Database project (http://rdp.cme.msu.edu/), imported in ClustalW2 for multiple sequence alignment (24) and compared with the partial 16S rDNA sequences obtained from the isolates.
DNA extraction protocol. Genomic DNA of all the pathogens from ATCC and CBMRN were extracted with the DNeasy Blood and Tissue Kit (Qiagen, Mississauga, Ontario, Canada). Independent DNA extractions were carried out on duplicate cultures, containing approximately 2Ã-109 cfu/ml, to assess the influence of the slight variations in DNA quantity and quality due to the extraction on the downstream analyses. The DNA samples obtained were then measured with a Nanophotometer (Montreal Biotech Inc.) to ensure presence of sufficient quantity and quality of DNA.
Amplification of 16S rRNA gene using real-time PCR. Real-time PCR amplification of a 16S rRNA gene fragment including the variable region V5 and V6 was performed using the BioRad CFX thermal cycler using the primer pairs p822 (5'-AGGATTAGATACCCTGGTAG-3') and p1100 (5'-AGCTGACGACARCCATGC-3') with a resulting amplicon of 295bp. For the CNS species, 16S rRNA gene fragment including the variable region V1 and V2 was used and the primers were p104 (5'-GCGGACGGGTGAGTAACAC-3') and p299 (5'- CCGATCACCCTCTCAGGTC-3') resulting in a 222bp amplicon. Bacterial genomic DNA (20 ng) was added to reaction mixture containing 0.25 ÂµM of each primer, 10Âµl of Evagreen mix and ultrapure distilled water (DNAse and RNAse free, Invitrogen) made up to 20Âµl. Each genomic DNA extract was tested in duplicate to further determine the reproducibility of the differences observed in their melting profiles. All reactions were performed in Multiplate PCR plates, low 96-well clear (catalog.no.MLL9601, Bio-Rad, Canada) and sealed with Microseal 'B' film (catalog.No.MSB1001, Bio-Rad, Canada). The cycling conditions were as follows, denaturing at 98Â°C for 2 min, followed by 40 two-step cycles of 98Â°c for 5 sec and annealing/extension at 55Â°C for 10 sec. A final denaturing step at 95Â°C for 1 min cool down to 70Â°C for 1 min was followed by the gradual temperature increase from 70 to 95Â°C with temperature increments of 0.2Â°C with each time a 10 sec hold to generate the melt curve. In case of CNS, the annealing temperature was set at 58Â°C. The melt curves obtained were analysed with Bio-Rad CFX Manager Software V.1 (Fig. 1 A & B) and the HRMA profiles were further evaluated with Precision Melt Analysis Software (Bio-Rad). Only when specifically mentioned, heteroduplex formation was used to identify the organisms which had similar clustering by adding equal amounts of genomic DNA of a chosen species to the isolated DNA template. This "heteroduplex effect" which is caused by the formation of mismatched hybrids (heteroduplexes) has a much greater influence on the shape of the melt curve than on its absolute melting temperature (Tm).
Each post-PCR amplicon was subjected to HRMA with the help of Precision melt software (Bio-Rad). HRMA for each extracted DNA sample was performed in duplicate and analyzed using the Precision melt software. The clustering of melt curves was based on regions of the melt curve corresponding to the line prior to melt of the double stranded DNA (pre-melting region), during the melting and after the complete separation of the double strands (post-melting region). The pre- and post-melting regions were optimized to attain the best clustering. In the case of the V5-V6 region of the 16S rRNA gene, the pre-melting region was set to include the portion of the curve between 78.4 and 79.0°C and the post-melting region to the portion between 88.5 and 88.8°C. Melting curves were normalized to relative values of 100 to 0% to eliminate the differences in intensity of fluorescence between reactions. The normalized melt curves were also evaluated after they were temperature-shifted along the temperature axis so that they met at a specific temperature at which the DNA became denatured.
The 16S alignments were aligned and compared, and a cladogram was created using the ClustalW program (www.ebi.ac.uk/clustalw) (Fig. 3). Differences in the variable sequence region of the 16S rDNA sequences between these bacterial species were targeted to generate discriminating melt and difference curves (Fig. 2 A & B). The V1-V2 region was chosen because of the genetic differences among the most common CNS in this region (Table 2). In the case of the V1-V2 region of the 16S rRNA gene, the pre-melting region was set to include the portion of the curve between 80.4 and 80.9°C and the post-melting region to the portion between 85.7 and 86.5°C.
HRMA of common mastitis pathogens.
Sequencing of the 16S rRNA gene fragment of all isolates confirmed that the amplicons corresponded to the expected 16s rDNA sequences in the Ribosomal database. With the melting profile of S. aureus as reference, difference plots of the various mastitis pathogens were generated that coincided with the corresponding sequence alignment given in supplementary Fig. 1. Streptococcus agalactiae and Streptococcus dysgalactiae were found to have 287 (97%) nucleotides in common in the particular amplicon. This similarity was evident in the HRMA and they were distinguishable as indicated by different colors (blue and green) in Fig. 2A and B. Staphylococcus aureus and Fusobacterium necrophorum could not be distinguished by the HRMA as they clustered together, even though they were genetically different (235/295) in the selected amplicon. These two species could be differentiated further by heteroduplexing with the PCR amplicon of S. aureus (data not shown).
Both the cladogram and HRMA indicated that Mycoplasma bovis was the most distant species in the group. The presented data showed that each bacterial species had a characteristic difference plot in the HRMA with minimal inter-and intra-run variability. The bacterial species that could be identified directly by their difference plots were S. agalactiae, S. dysgalactiae, S. uberis, A. pyogenes, C. bovis, E. coli, P. melaninogenica, B. fragilis, and M. bovis.
HRMA of CNS pathogens. HRMA on V5-V6 region of the 16S rRNA gene was not satisfactory to differentiate the important CNS in the present study. Staphylococcus aureus and Staphylococcus capitis could not be differentiated in the HRMA as their melt curves clustered together (Fig. 4). The sequence alignment of the 16S rDNA sequences (V1-V2 region) of the important CNS in milk revealed that there was high nucleotide sequence identity between the sequences of S. aureus and S. capitis (Table 2). Sequence analysis comparison of S. aureus with respect to S. capitis revealed T to C position at 183, 205 and 219 and A to G position at 186. Staphylococcus aureus with respect to Staphylococcus epidermidis revealed a T to A position at186, A to T position at 205, C to T position at 219 and A to G position at 292. Staphylococcus saprophyticus and Staphylococcus xylosus differed only by a single nucleotide at position 188 (G to A) but in the HRMA, S. saprophyticus had a melt curve closer to Staphylococcus cohnii than S. xylosus which differed by 5 nucleotides. Staphylococcus hominis and S. haemolyticus, and Staphylococcus hyicus and Staphylococcus intermedius differed among each other by 3 nucleotides. Their melt curves were also found relatively close together (Fig. 4). HRMA applied to V1-V2 hypervariable region of the 16S rRNA gene was able to discriminate between all CNS included in this study.
In this study, we describe a novel and powerful scheme combining broad-range real-time PCR and high-resolution melt analysis for rapid species identification of mastitis pathogens. The regions V5-V6 of 16S rRNA gene for common mastitis pathogens and V1-V2 for CNS were selected based on the sequence diversity among the different bacterial species used in the study. Species specific sequences within a given hypervariable region constituted useful targets for diagnostic assays (11). Without multiplexing or hybridization probes, the present technique only required 90 min each for the identification of CNS and the other common mastitis pathogens. HRMA applied to V5-V6 hypervariable region of the 16S rRNA gene enabled discrimination of 9 of the 13 major mastitis pathogens at a single step, including the anaerobes such as P. melaninogenica, B. fragilis, and M. bovis. Both the cladogram and HRMA indicated that M. bovis was the most distant species in the group. This may be due to the low G and C content as well as the low melting temperature (82.8°C) of its DNA.
Staphylococcus aureus shared a similar melt curve with F. necrophorum. On subsequent heteroduplexing, S. aureus and F. necrophorum could be differentiated by the shift of melt curves. Despite the high discriminatory precision of HRMA, we found that amplicons of relatively different sequences may generate similar melt curves. This finding is in agreement with findings published previously (12).
HRMA could differentiate all CNS included in this study based on the melt curves, suggesting that 16S rRNA gene has enough discriminatory power within these genera. In the present study, S. aureus could not be differentiated from S. capitis as both took similar color curves. The melt curve of S. capitis was close to the curve of S. epidermidis. Staphylococcus capitis and S. epidermidis constituted a group of related species on the basis of 16S rRNA sequences and this is in agreement with the results earlier described in PCR-sequencing assays targeting the 16S rRNA gene (21).
Using the second HRMA described in this study, S. intermedius could be discriminated from S. aureus. As per the NCBI database, the selected sequence covering the V1-V2 region of the 16S RNA gene of S. intermedius had 100% identity with that of Staphylococcus pseudintermedius. Staphylococcus pseudintermedius is generally confused with S. aureus in phenotypic identification (22). The findings in the present study suggest the feasibility of HRMA in discriminating S. aureus from S. pseudintermedius. Therefore, routine genotyping through this more discriminating approach might give insights into the involvement of specific staphylococci spp. in diverse clinical situations and diseases.
Staphylococcus saprophyticus and S. xylosus differed only by a single nucleotide at position 188 (G to A), but in the HRMA, the former had a melt curve closer to S. cohnii than S. xylosus which differed by 5 nucleotides. This finding is in agreement with phylogenetic studies performed earlier with 16S and tuf sequence analysis (21).
The findings of the present study suggest HRMA as a simple and efficient alternative to the cumbersome culture and subsequent species identification of bacterial mastitis pathogens. The identification of pathogens in mastitis milk samples using HRMA could be undertaken in two steps. The DNA extract from a suspected milk sample can be subjected to HRMA along with DNA extracts from common mastitis pathogens as positive controls. As CNS are identified as pathogens only in approximately 5% of clinical mastitis cases (30), a second HRMA may be attempted with CNS as positive control, if the first one fails. Since HRMA was validated in the present study using bacterial DNA extracts from pure cultures, additional validation using DNA extracts from milk samples obtained from clinical and subclinical mastitis cases is necessary.
Misidentification of bacterial species in clinical samples using HRMA can occur due to a few different reasons. First, when different bacterial species have the same DNA sequence within the selected PCR amplicon. This potential problem can be practically overcome by designing a second PCR that targets another fragment of 16S rRNA gene. The feasibility of this strategy was demonstrated by Cheng et al. in differentiating E. coli, Shigella flexneri, Salmonella enterica serovar typhimurium, and Salmonella enterica serovar enteritidis (12). The melt profiles were analyzed based on three (V1, V3 and V6) instead of one of 16S hypervariable regions (46).
A second reason for misinterpretation is the isolation of an uncharacterized bacterial species with a melting profile similar to another species in the database. This potential mistyping can be resolved by the use of a confirmation test of heteroduplex formation between the PCR products of the test sample and a standard strain of the putative bacterial species. When a test sample differs from the putative bacterial species, the melting plot will typically change after heteroduplex formation. No change to the melting plot occurs when a test sample matches the bacterial species of the standard strain. Alternatively, increasing the size of the high-resolution melt database by inclusion of a larger panel of pathogenic and nonpathogenic bacteria could help to rule out potential misidentification and cross-reactions with contaminants. A third issue is the heterogeneity of 16S rRNA gene within a bacterial species. Sequence variations between different members of the 16S rRNA gene within a bacterial isolate have been reported previously in Mycoplasma mycoides, Mycoplasma spp., and E. coli (6, 13, 23, 31).
Another limiting factor of this technique is that the precision and further analysis of the melting profiles is dependent on the presence of an initial DNA template of sufficient quality. Finally, identification by high-resolution melt analysis may be compromised by sample contamination or mixed infections when PCR is performed directly on clinical specimens. Whether high-resolution melt profiles, such as the presence of multiple melting peaks in the derivative plot, provide additional information for differentiating single versus multiple infections in clinical specimens is worthy of further investigation.
In conclusion, HRMA of 16S rDNA sequences of bovine mastitis pathogens is an attractive method as it offers several advantages over the methods that are currently in use and can supply timely information to physicians in a clinical laboratory setting. Although a traditional culture-based assay is relatively cost-effective, it usually requires at least 24 h to identify the bacteria via biochemical and phenotypic analysis. When combined with rapid-cycle PCR, high-resolution melt analysis requires minimal time and lower material costs.