Skip to main content
NCBI home page
Springer Nature - PMC COVID-19 Collection logoLink to Springer Nature - PMC COVID-19 Collection
. 2022 Dec 20;47(2):495–509. doi: 10.1007/s11259-022-10047-0

Comparison of PCR-HRM, colorimetric LAMP and culture based diagnostic assays in the detection of endometritis caused by Streptococcus equi subsp. zooepidemicus in mares

Charlotte Garner 1, Cyril Stephen 1,2, Sameer Dinkar Pant 1,2, Seyed Ali Ghorashi 1,2,✉
PMCID: PMC9765344  PMID: 36538151

Abstract

Streptococcus equi subsp. zooepidemicus (S. zooepidemicus) is one of the causative agents of equine endometritis. In this study, a panel of different bacterial species, and colonies derived from bacteriological cultures of 38 clinical samples, were subjected to Loop-Mediated Isothermal Amplification (LAMP) assay and PCR, followed by high-resolution melt (HRM) curve analysis. All clinical samples were genotyped into three distinct groups based on HRM curve analysis. Differences in melting curve profiles were a reflection of DNA variation in sorD gene which was confirmed by DNA sequencing. A mathematical model based on Genetic Confidence Percentage (GCP) was used in HRM curve analysis and a cut-off point value was established which differentiated S. zooepidemicus isolates without requiring visual interpretation of curve profiles. The accuracy of PCR-HRM and bacterial culture in detection of S. zooepidemicus were identical with 100% sensitivity and specificity, while LAMP assay had similar specificity but a lower sensitivity (89.5%). PCR-HRM and LAMP assay provided an effective detection method with a turn-around time of six hours for PCR-HRM and 120 min for LAMP assay, compared to a minimum three days that was required when routine bacteriological culture method was used. In summary, results indicate that LAMP had the quickest turnaround, and HRM curve analysis could potentially be used for genotyping without DNA sequencing. Any mare suspected of endometritis will benefit from developed rapid diagnostic tests for detection of S. zooepidemicus and proper treatment prior to being bred and will mitigate unnecessary treatment and antibiotic resistance.

Keywords: Streptococcus equi subsp. zooepidemicus, LAMP, PCR, High-resolution melt curve analysis, Bacterial culture, Comparison, Endometritis

Introduction

The Streptococcus equi subsp. zooepidemicus (S. zooepidemicus) is a Gram-positive bacterium that has been isolated from different species such as human, monkey, dog, cat, pig and horse (Bannister et al. 1985; Boyle et al. 2021; Frymus et al. 2015; Priestnall & Erles 2011; Soedarmanto et al. 1996). The S. zooepidemicus is considered as a normal flora of reproductive and upper respiratory system in horses but can cause pneumonia and endometritis as an opportunistic pathogen (Casagrande Proietti et al. 2011; Lavoie et al. 1994). However, it has been reported that S. zooepidemicus isolates from infectious endometritis in mares are genetically distinct from isolates from the caudal reproductive tract within the same mare, which shows that some strains are better adapted to colonise the endometrium.(Rasmussen et al. 2013).

Reproductive problems such as conception failure and embryo loss are a major issue for the equine industry and are often a result of endometritis (Nocera et al. 2017). Equine endometritis caused by S. zooepidemicus produces an inflammatory response within the uterus, which is a threat to the fertility potential of brood mares. An infection of this nature before or during gestation significantly increases the risk of embryonic loss and failure to conceive and may lead to clinical subfertility or infertility (Pasolini et al. 2016). However, persistent inflammation that is left undetected and untreated will lead to chronic fertility issues, resulting in economic losses (Canisso et al. 2020). Due to the relatively short equine breeding season, veterinarians are often under pressure to breed mares during the early part of the breeding season. In the thoroughbred industry, mares need to be free from any infectious or venereal bacterial pathogens before they are sent to the stud for natural mating. One of the diagnostic methods for the detection of S. zooepidemicus is bacterial culture, and differentiation of S. zooepidemicus and S. equi based on fermentation testing of carbohydrate such as lactose, sorbitol and trehalose (Bannister et al. 1985). Unlike S. zooepidemicus, S. equi strains are not capable of fermenting sorbitol due to the loss of the sorD gene (Holden et al., 2009). Therefore, molecular differentiation of these species would be possible based on this difference in their genome (Kinoshita et al. 2014). Endometrial swabbing for culture is the gold standard test to confirm an infection however this takes 3–5 days to be completed and given the short equine breeding season, the mares may miss the opportunity to be bred early during the breeding season. Molecular diagnostic assays such as PCR can provide results with higher sensitivity than cultures and results can be ready within 6 h with regards to anaerobic, aerobic and slow-growing bacteria (Båverud et al. 2007; Bohn et al. 2014; Noll et al. 2020; North et al. 2014). PCR followed by high resolution melt (HRM) curve analysis is a technique for detecting DNA sequence variations based on differences in the melting curves of PCR amplicons and is quickly becoming the alternative method of detection and genotyping of pathogens (Das et al. 2020; Ghorashi et al. 2010; Young et al. 2021). PCR-HRM allows for rapid detection of nucleotide variation in the amplified target DNA sequences. To our knowledge, such a PCR-HRM curve analysis has not been reported for genotyping of S. zooepidemicus. Loop-mediated isothermal amplification (LAMP) is a molecular diagnostic method that uses four to six primers and can be performed in a single temperature. This technique has been developed as an alternative method for amplification of DNA for detection of a number of microorganisms including S. zooepidemicus (Kinoshita et al. 2014). The aim of this study was to develop a PCR-HRM assay and compare results with bacterial culture and LAMP assay in detecting S. zooepidemicus in tested samples.

Materials and methods

Animal ethics and sample collection

Approval for the use of opportunistic samples from mares was granted by the CSU Animal Care and Ethics Committee (Protocol number A19251) and all experiments were performed in accordance with the relevant guidelines and regulations.

Endometrial swab samples were collected from mares presented to the Veterinary Clinical Centre (VCC) at Charles Sturt University (CSU) and the Riverina Equine Veterinary Services (REVS), Wagga Wagga and cultured at Veterinary Diagnostic Laboratory (CSU). Cultured samples were used to develop or optimise the diagnostic assays.

Bacterial reference cultures (samples 1–15) were used for optimisation of the assays (Table 1).

Table 1.

Source of samples, bacterial species, mean curve peak melting points, genotypes and results of bacterial culture, PCR and LAMP assay

Sample number Isolate ID Source Bacterial species Number of times tested Melting Temperature
Mean ± SD		 Mean GCP ± SD Genotyped by HRM PCR LAMP assay GenBank accession number/Genotyped by sequencing
1 WW 19 − 07 Reference strain Escherichia coli 9 NMC1 2.89 ± 0.1 Variation NA2
2 WW 19 − 08 Reference strain Pseudomonas aeruginosa 9 NMC 1.64 ± 0.02 Variation NA
3 WW 19 − 09 Reference strain Klebsiella pneumoniae 9 NMC 1.42 ± 0.01 Variation NA
4 WW 19 − 10 Reference strain Enterobacter cloacae 9 NMC 1.31 ± 0.02 Variation NA
5 WW 19 − 01 Reference strain Streptococcus equi subsp. zooepidemicus 9 83.95 ± 0.07 99.56 ± 0.0  S. zooepidemicus + + MW207312 / S. zooepidemicus
6 WW 19 − 02 Reference strain Streptococcus equi subsp. zooepidemicus 9 84.15 ± 0.3 73.67 ± 2.34  S. zooepidemicus + + MW207313 / S. zooepidemicus
7 WW 19 − 11 Reference strain Pasteurella multocida 9 NMC 3.02 ± 0.12 Variation NA
8 WW 19 − 12 Reference strain Pseudomonas aeruginosa 9 NMC 1.55 ± 0.31 Variation NA
9 WW 19 − 03 Reference strain Streptococcus equi subsp. zooepidemicus 9 83.8 ± 0.06 91.72 ± 4.72  S. zooepidemicus + + MW207314 / S. zooepidemicus
10 WW 19 − 04 Reference strain Streptococcus equi subsp. zooepidemicus 9 84.06 ± 0.05 93.34 ± 2.61  S. zooepidemicus + + MW207315 / S. zooepidemicus
11 WW 19 − 05 Reference strain Streptococcus equi subsp. zooepidemicus 9 84.25 ± 0.0 63.89 ± 3.41  S. zooepidemicus + + MW207316 / S. zooepidemicus
12 WW 19 − 13 Reference strain Campylobacter coli 9 NMC 4.21 ± 0.01 Variation NA
13 WW 19 − 14 Reference strain Campylobacter jejuni 9 NMC 3.22 ± 0.04 Variation NA
14 WW 19 − 15 Reference strain Staphylococcus aureus 9 NMC 4.65 ± 0.02 Variation NA
15 WW 19 − 06 Reference strain Streptococcus equi subsp. zooepidemicus 9 83.91 ± 0.07 98.02 ± 1.40  S. zooepidemicus + + MW207317 / S. zooepidemicus
16 CS 19-3436/1 Uterine Swab Escherichia coli (non-haemolytic) 5 NMC 3.61 ± 1.6 Variation NA
17 CS 19-3436/2 Uterine Swab Streptococcus equi subsp. zooepidemicus 5 84.35 ± 0.0 98.95 ± 0.04  S. zooepidemicus + + OL850024 / S. zooepidemicus
18 CS 19-3505 Uterine Swab Citrobacter koseri 5 NMC 1.85 ± 0.03 Variation NA
19 CS 19-3506 Uterine Swab Enterococcus sp. 5 NMC 2.07 ± 1.02 Variation NA
20 CS 19-3506/2 Uterine Swab Staphylococcus sp. 5 NMC 2.16 ± 0.80 Variation NA
21 CS 19-3786 Wound Swab Streptococcus equi subsp. zooepidemicus 5 84.53 ± 0.05 80.99 ± 3.40  S. zooepidemicus + + MW207318 / S. zooepidemicus
22 CS 19-4086 Eye Swab Streptococcus equi subsp. zooepidemicus 5 84.86 ± 0.2 33.3 ± 2.4  S. zooepidemicus + + MW207319 / S. zooepidemicus
23 CS 19-4090 Uterine Swab Escherichia coli (non-haemolytic) 5 NMC 2.29 ± 0.85 Variation NA
24 CS 19-4106 Umbilical Swab Streptococcus equi subsp. zooepidemicus 5 84.4 ± 0.0 97.71 ± 1.04  S. zooepidemicus + + OL850025 / S. zooepidemicus
25 CS 19-4211 Uterine Swab Streptococcus equi subsp. zooepidemicus 5 84.35 ± 0.0 98.28 ± 0.35  S. zooepidemicus + + MW207320 / S. zooepidemicus
26 CS 19-4279/1 Uterine Lavage Fluid Klebsiella pneumoniae 5 NMC 2.36 ± 0.72 Variation NA
27 CS 19-4279/2 Uterine Lavage Fluid Escherichia coli (non-haemolytic) 5 NMC 2.75 ± 0.96 Variation NA
28 CS 19-4288 Uterine Lavage Fluid Klebsiella aerogenes 5 NMC 2.26 ± 0.57 Variation NA
29 CS 19-4353 Uterine Swab Streptococcus equi subsp. zooepidemicus 5 84.36 ± 0.02 99.66 ± 0.28  S. zooepidemicus + + MW207321 / S. zooepidemicus
30 CS 19-4535 Uterine Lavage Fluid Streptococcus equi subsp. zooepidemicus 5 84.35 ± 0.0 99.77 ± 0.24  S. zooepidemicus + + MW207322 / S. zooepidemicus
31 CS 19-4610/1 Uterine Swab Streptococcus equi subsp. zooepidemicus 5 84.40 ± 0.0 97.64 ± 0.79  S. zooepidemicus + + OL850026 / S. zooepidemicus
32 CS 19-2849 Not Recorded Streptococcus equi subsp. zooepidemicus 5 84.03 ± 0.05 53.94 ± 14.48  S. zooepidemicus + + MW207323 / S. zooepidemicus
33 CS 19-3337 Blood Streptococcus equi subsp. zooepidemicus 5 84.46 ± 0.05 95.96 ± 2.07  S. zooepidemicus + + OL850027 / S. zooepidemicus
34 CS 19-3361 Blood Streptococcus equi subsp. zooepidemicus 5 84.61 ± 0.02 72.28 ± 7.33  S. zooepidemicus + + MW207324 / S. zooepidemicus
35 CS 19-3402 Uterine swab Pseudomonas aeruginosa 5 NMC 3.32 ± 3.03 Variation NA
36 CS 17–0107 Not Recorded Streptococcus equi subsp. zooepidemicus 5 83.95 ± 0.08 45.87 ± 6.14  S. zooepidemicus + + OL850028 / S. zooepidemicus
37 CS 17–0281 Not Recorded Streptococcus equisimilis 5 NMC 0.51 ± 0.49 Variation NA
38 CS 17–0519 Not Recorded Streptococcus equi subsp. zooepidemicus 5 83.91 ± 0.20 46.4 ± 30.92  S. zooepidemicus + + MW207325 / S. zooepidemicus
39 CS 19–0354 Not Recorded Streptococcus equi subsp. zooepidemicus 5 84.5 ± 0.0 53.88 ± 2.83  S. zooepidemicus + + MW207326 / S. zooepidemicus
40 CS 19–0578 Not Recorded Streptococcus equi subsp. zooepidemicus 5 84.08 ± 0.23 99.56 ± 0.1  S. zooepidemicus + + OL850029 / S. zooepidemicus
41 CS 19-1862 Not Recorded Streptococcus equi subsp. zooepidemicus 5 83.95 ± 0.26 79.69 ± 8.4  S. zooepidemicus + + OL850030 / S. zooepidemicus
42 CS 19-2242 Not Recorded Streptococcus equi subsp. zooepidemicus 5 84.06 ± 0.05 99.26 ± 0.30  S. zooepidemicus + + MW207327 / S. zooepidemicus
43 CS 19-2654 Not Recorded Streptococcus equi subsp. zooepidemicus 5 84.25 ± 0.0 84.57 ± 2.64  S. zooepidemicus + MW207328 / S. zooepidemicus
44 CS 19-4950/2 Uterine Swab Streptococcus equi subsp. zooepidemicus 5 83.91 ± 0.07 87.54 ± 6.24  S. zooepidemicus + MW207329 / S. zooepidemicus
45 CS 19-4970/1 Umbilicus Streptococcus equi subsp. zooepidemicus 5 83.9 ± 0.09 89.30 ± 1.14  S. zooepidemicus + + OL850031 / S. zooepidemicus
46 CS 19-4983 Uterine Swab Streptococcus equi subsp. zooepidemicus 5 84.03 ± 0.05 98.03 ± 1.28  S. zooepidemicus + + OL850032 / S. zooepidemicus
47 CS 20–0035 Surgical Site Swab Streptococcus equi subsp. zooepidemicus 5 84.25 ± 0.0 82.29 ± 2.29  S. zooepidemicus + + OL850033 / S. zooepidemicus
48 CS 19-4649 Uterine Swab Streptococcus equi subsp. zooepidemicus 4 84.25 ± 0.0 88.17 ± 3.29  S. zooepidemicus + + OL850034 / S. zooepidemicus
49 CS 19-4754/1 Joint Fluid Streptococcus equi subsp. zooepidemicus 4 84.46 ± 0.05 50.11 ± 7.0  S. zooepidemicus + + MW207330 / S. zooepidemicus
50 CS 19-4860 Uterine Swab Streptococcus equi subsp. zooepidemicus 4 84.0 ± 0.0 94.9 ± 0.0  S. zooepidemicus + OL850035 / S. zooepidemicus
51 CS 20-2774 Not Recorded Pseudomonas aeruginosa 4 NMC 3.73 ± 0.51 Variation NA
52 CS 20–0262 Wound Swab Streptococcus equi subsp. zooepidemicus 3 84.46 ± 0.38 82.74 ± 21.43  S. zooepidemicus + OL850036 / S. zooepidemicus
53 CS 20-1011/2 Nasolacrimal punctum swab Streptococcus equi subsp. zooepidemicus 3 84.25 ± 0.0 78.10 ± 10.55  S. zooepidemicus + + OL850037 / S. zooepidemicus
Open in a new tab

1 = No Melt Curve, 2 = Not Applicable

Clinical samples collected from equine stud farms consisted of 38 samples including 14 uterine swabs, four uterine lavage fluid samples (collected in 50 ml tubes) and 20 clinical samples from different sources that Streptococcus equi subsp. zooepidemicus was isolated from them (Table 1, samples 16–53). All samples were transported to the laboratory in a ski with ice packs.

Within eight hours of sample collection, swab samples were smeared onto blood agar plates (Thermo Fisher Scientific™, Australia) and incubated at 37 °C for 24 h. The S. zooepidemicus colonies were identified based on Garm-positive staining and ability to ferment lactose, sorbitol and ribose but not trehalose. Uterine fluid samples were centrifuged at 1,000 rpm for 10 min, the supernatant discarded, and precipitate was smeared onto blood agar plates as above.

DNA extraction and quantification

A colony from each S. zooepidemicus isolate/strain was used for DNA extraction using Wizard® Genomic DNA Purification Kit (Promega, Australia) as per the manufacturer’s instructions. Briefly, a colony was added to lysis buffer and incubated at 80° C for 10 min. The lysate was added to mini-column assembly and centrifuged 13,000 g for 3 min. The mini-column was washed four times with washing buffer and DNA was eluted using distilled water. The quality and quantity of the extracted DNA was measured using a Nanodrop 2000 (Thermo Scientific, Australia).

Detection of S. zooepidemicus using PCR

The sorD gene was chosen for designing PCR primers and amplification. This was based on the previous reports that all the S. zooepidemicus strains possess this gene while all S. equi strains lack this gene (Holden et al. 2009). In addition, there are a number of nucleotide variations in this gene among S. zooepidemicus strains which can be used for differentiation of isolates. A pair of oligonucleotide primers, St-equi-F (5’- AGATCGCTCAAGTTATATTACG-3’) and St-equi-R (5’-TTAGCAAGGGTCTGTGCA-3’), flanking the target region was designed with the PCR amplicon expected to yield a product of 199 bp. The concentration of DNA samples was adjusted to 5 ng/µl for all PCR reactions. PCR amplification was performed in 25 µl reaction volume on a Rotor-Gene™ 6000 thermal cycler. The reaction mixture contained 10 ng of extracted genomic DNA (2 µl), 2 µM of each primer (2 µl), 1.5 mM MgCl2 (1.5 µl) 1250 µM of each dNTP (4 µl), 5 µM Syto9 green fluorescence nucleic acid stain (2 µl) (Invitrogen, Australia), 5 x GoTaq Green Flexi Reaction Buffer (5 µl ), 1 U of Go Taq DNA Polymerase (1 µl) (Promega, Australia) and 7.5 µl distilled water. PCR cycling consisted of one cycle of 94 °C for 3 min, 34 cycles of 94 °C for 30 s, 56 °C for 30 s and 72 °C for 30 s, and a final cycle of 72 °C for 5 min. All samples were tested in triplicates and in each set of PCR reactions, S. zooepidemicus (WW 19 − 01) genomic DNA and distilled water were used as positive and negative controls, respectively.

HRM curve analysis

After each PCR run was completed, analysis of the HRM curves were performed and all samples in each HRM run were subjected to three different ramping times of 0.1, 0.3 and 0.5 °C s-1 between 50 and 99 °C. The PCR-HRM curve analysis was performed with each sample tested in triplicates. The HRM curves were normalised using the temperature range of 79-80 °C and 88-89 °C and the melt profiles from each run were analysed using Rotor-Gene 1.7.27 software (Qiagen). Differentiation between bacterial species and subspecies was carried out based upon the melting points and shape of conventional and normalised curves, respectively.

The S. zooepidemicus strain (WW 19 − 01) was used as the reference genotype and the average HRM genotype confidence percentage (GCP) was predicted. The GCP value which is calculated by the software for each sample could be between 0 and 100% and is calculated based on the similarity of the DNA melting points compared to that of the reference genotype. The value of 100% demonstrates the highest similarity with the reference genotype.

The GCPs for known S. zooepidemicus isolates were averaged and the standard deviation (SD) was calculated and used to establish the GCP range for S. zooepidemicus cut-off point. The cut-off point was applied in HRM analysis to evaluate the differentiation power of the test to discriminate the bacterial isolates. Following HRM analysis, all PCR products were subjected to gel electrophoresis to confirm the size of amplicon prior to DNA sequencing.

Sequencing of PCR amplicons

Selected amplicons were sent to the Australian Genome Research Facility Ltd (AGRF Ltd., Brisbane, Australia) for sequencing in both directions using F3 and B3 primers. The ClustalW software (Thompson et al. 1994) and BioEdit Sequence Alignment Editor (version 6.0.9.0) were used to analyse sequence data. GenBank accession numbers were assigned to the nucleotide sequences of the tested isolates and reference strains (Table 1).

Loop-Mediated Isothermal Amplification (LAMP) Protocol

Primers used for LAMP assay have been previously published (Kinoshita et al. 2014). The LAMP master mix contained 10 µl of WarmStart colorimetric 2X Master Mix (Cat. No. M1800L, New England Biolabs, Australia), published primers (Kinoshita et al. 2014) including F3 and B3 each at 2 µM concentration as the outer primers, two inner primers (FIP and BIP) at 16 µM each and a loop primer (LB) at 4 µM concentration were used in LAMP assay. Two µL DNA (10 ng) were finally added to make a total volume of 20 µL. LAMP reactions were incubated in a heat block at 65 °C for 60 min and results were determined by visual observation of the colorimetric change of the solutions. A positive reaction detecting S. zooepidemicus DNA in the sample exhibited a colour change from red to yellow and all negative samples remained red in colour.

Analysis of assay sensitivity, specificity, and limit of detection

The sensitivity of PCR and LAMP was examined using serial ten-fold dilutions of DNA extracted from the reference strain (WW 19 − 01). The DNA dilutions ranged from 1ng/µl to 1 × 10− 7ng/µl. Each DNA dilution was tested using both PCR and LAMP assays. To evaluate specificity of these assays, DNA was extracted from a panel of different bacterial strains (Klebsiella pneumoniae subsp. Pneumoniae MGH78578 (ATCC 700,721), Klebsiella aerogenes 1,101,371 (ATCC BAA-2356), Pseudomonas aeruginosa 109,246 (ATCC BAA-1744), Enterobacter cloacae 1,000,654 (ATCC BAA-2468), Campylobacter coli CIP 7080 (ATCC 33,559), Campylobacter jejuni VPI H840 (ATCC 29,428), Staphylococcus aureus HFH-29,744 (ATCC BAA-1690), Citrobacter koseri 4225-83 (ATCC BAA-895), Escherichia coli 1,100,101 (ATCC BAA-2471) and Pasteurella multocida subsp. multocida M-2283 (ATCC 21,955)) and tested in each assay. Accuracy of PCR and LAMP assay were calculated and compared with the bacterial culture which was considered as the gold standard test for detection of S. zooepidemicus. The sensitivity and specificity of each diagnostic assay was calculated using MEDCALC 2 × 2 contingency table (www.medcalc.org/calc/diagnostic_test.php).

Results

Detection and identification of S. zooepidemicus isolates using PCR-HRM

PCR was optimised using reference bacterial strains (samples 1–15 in Table 1) and a single DNA fragment of expected size (about 200 bp) was identified in all 33 S. zooepidemicus strains/isolates, including six S. zooepidemicus reference strains and 27 clinical isolates that were recovered by culture, in gel electrophoresis. No DNA amplification was observed in other bacterial strains.

On completion of PCR, amplicons from all samples were subjected to HRM curve analysis. Visual assessment of generated curves in three different rampings revealed that 0.5 °C s− 1 provided better visualisation of the conventional and normalised melt curves (Fig. 1). All S. zooepidemicus samples produced one peak in their conventional melt curves between 83.75 and 84.65 °C (Fig. 1; Table 1). All S. zooepidemicus specimens produced three distinct conventional and normalised HRM curves. All other bacterial species did not produce a melt curve. Comparison of melting temperatures of tested samples in different PCR runs on different days showed slight variation in melting temperatures while there was no change to the shape of conventional and normalised melt curves. The mean and standard deviation (SD) of the melting point temperatures of produced peak and the mean GCP and SD generated from several runs of PCR and HRM curve analysis for all samples including reference strains are shown in Table 1.

Fig. 1.

Fig. 1

Open in a new tab

Conventional and normalised melt curve analysis of S. zooepidemicus strains and isolates. a Conventional and b normalised melt curve analysis of PCR amplicons

Non-subjective differentiation of S. zooepidemicus isolates using high-resolution melt curve analysis based on genotype confidence percentage values

The GCP values produced by S. zooepidemicus reference strains were used to generate a mathematical model for differentiation of S. zooepidemicus specimens. This model was used to evaluate the genotype of the field isolates without using visual interpretation of melt curves (subjective).

The mean and SD values of 186 GCP values from 33 specimens of S. zooepidemicus strains and isolates was 81.1 ± 20.3. The cut-off point was calculated by subtracting the 3 × SD from the mean GCP (81.1- (3 × 20.3) = 20.2). The cut-off point was calculated to be 20.2. This means that all samples which produce the GCP value ≥ 20.2 are predicted to be S. zooepidemicus and samples with GCP value less than cut-off point are more likely not related to S. zooepidemicus.

All amplicons generated from S. zooepidemicus strains produced GCPs in a range of 33.3 and 99.7, and since this was greater than cut-off point (20.2), all were genotyped automatically as S. zooepidemicus. All other bacterial strains (non-S. zooepidemicus strains) had GCPs less than cut-off point value between 0.51 and 4.65 and were automatically identified as “variation” (Table 1). The gap between the lowest S. zooepidemicus and highest non-S. zooepidemicus samples was 28 GCP (Fig. 2).

Fig. 2.

Fig. 2

Open in a new tab

Comparison of the distribution of GCPs from S. zooepidemicus and non-S. zooepidemicus strains by dot plot

The mathematical method and cut-off point used in this study can help with the detection of the S. zooepidemicus and intraspecies in samples without visual evaluation of the HRM curves particularly when large number of samples are to be tested.

Detection of minor variations in sorD gene nucleotide sequences by PCR-HRM curve analysis

To confirm that differences identified in HRM melting curves are associated with variation in nucleotide sequences, amplicons from samples of each distinct curve profile were selected and sequenced. Using BioEdit alignment tool, the sequences were analysed (Fig. 3).

Fig. 3.

Fig. 3

Open in a new tab

Sequence alignment of amplicons of PCR for selected S. zooepidemicus isolates. Identical nucleotides are shown by ‘.’

There were three to seven nucleotide variation within 199 nucleotides in the amplicon that resulted in the three distinct curve profiles of S. zooepidemicus (Fig. 3). Eleven strain/isolates produced a distinct group. While ten isolates in this group (WW 19 − 05, WW 19 − 06, WW 19 − 04, WW 19 − 03, CS10-4535, CS19-4353, CS19-4211, CS19-3361, CS19-2654 and CS19-2242) had similar DNA sequences, one isolate (CS19-4754-1) showed a nucleotide substitution (A to G) at position 43 of the sequence. Four isolates/strains (CS19-0354, CS19-3786, WW 19 − 01 and WW 19 − 02) had identical sequences and produced the second group. A sample from this group (WW 19 − 01) was used as reference strain in this study. The third group contained four isolates, three showed identical sequences (CS17-0519, CS19-2849 and CS19-4950-2) and one isolate (CS19-4086) had one nucleotide substitution (T to G) at position 65 of the sequence. The two melt curve profiles that were closely related showed 3 nucleotide variations in their sorD gene sequence.

The phylogenetic analysis based on multiple sequence alignment of targeted segment of sorD gene sequences (using Molecular Evolutionary Genetics Analysis (MEGA) software), placed S. zooepidemicus samples in three separate clades (Fig. 4). Samples within each of these three clades were corresponding to the three HRM melt curves.

Fig. 4.

Fig. 4

Open in a new tab

Phylogenetic relationship of selected samples based on the partial sequence of the sorD gene. The tree was constructed using Neighbor-Joining method with bootstraps values shown next to the branches. Labels at branch tips refer to sample ID followed by GenBank accession numbers

Detection of S. zooepidemicus isolates using LAMP assay

The DNA isolated from five S. zooepidemicus reference strains (WW 19-01-WW 19 − 05), and 23 out of 27 S. zooepidemicus isolates were successfully amplified in the LAMP assay, inducing a change of reaction colour from red to yellow. LAMP failed to detect four positive specimens (CS 19-2654, CS 19-4950/2, CS-19-4860 and CS 20–0262) showing no change of colour to yellow in LAMP reaction mixture (Table 1).

The limit of detection and specificity of PCR and LAMP assay

The limit of detection and specificity of both assays were evaluated by the minimal DNA quantity which could be detected in each assay and results from testing unrelated bacterial strains.

The detection limit of PCR and LAMP assay was evaluated using 10-fold serial dilutions of DNA extracted from S. zooepidemicus reference strain (WW 19 − 01) ranging from 2ng to 2 × 10− 7ng. The results showed that the target DNA could be detected up to 2 × 10− 2 ng by PCR and 2 × 10− 3 ng in LAMP assay, indicating that LAMP assay is 10 times more sensitive than PCR in detection of S. zooepidemicus pure DNA.

When a panel of unrelated bacterial strains (Klebsiella pneumoniae, Klebsiella aerogenes, Pseudomonas aeruginosa, Enterobacter cloacae, Campylobacter coli, Campylobacter jejuni, Staphylococcus aureus, Citrobacter koseri, Escherichia coli and Pasteurella multocida) were tested in both assays, all of these bacterial samples were negative in PCR and LAMP assay.

The specificity of PCR was determined to be 100% as confirmed by DNA sequencing of S. zooepidemicus amplicons. LAMP assay showed similar specificity.

The accuracy of PCR and LAMP assay in detection of S. zooepidemicus in cultured samples was measured through MEDCALC 2 × 2 contingency table using bacterial culture-based diagnosis as the gold standard test. The PCR showed 100% sensitivity (95% CI, 0.90-1.00) and 100% specificity (95% CI, 0.72-1.00) similar to bacterial culture-based diagnosis. The LAMP assay showed 89.5% sensitivity (95% CI, 0.75–0.97) and 100% specificity (95% CI, 0.72-1.00) in detection of S. zooepidemicus.

HRM curve analysis was able to genotype S. zooepidemicus samples while LAMP assay was not designed to be capable of bacterial typing.

Discussion

The S. zooepidemicus is an opportunistic pathogen, widely associated with equine endometritis and can cause a variety of other diseases such as placentitis and mastitis (Kinoshita et al. 2014). Mares are required to be free from any venereal bacterial infection before mating.

Without efficient diagnosis and treatment from a veterinary professional, the condition can persist and become chronic, negatively impacting breeding and performance and leading to significant economic losses for the equine industry (Casagrande Proietti et al. 2011). Bacterial culture and PCR are routinely used for diagnostic purposes. However, results might be available within 3–5 days and since the breeding season is relatively short, a point-of-care diagnostic method such as LAMP which can provide results within two hours could be helpful. The identification of S. zooepidemicus isolates via bacteriological culture was based on the ability of these isolates to ferment sorbitol and ribose, but not trehalose (Holden et al. 2009). Isolates identified as S. zooepidemicus were subsequently confirmed by sequencing of PCR amplicons and HRM analysis. However, it should be noted that not all S. zooepidemicus isolates ferment ribose and sorbitol, and therefore, it is possible that such S. zooepidemicus isolates may not have been identified via bacteriological culture (Silva et al. 2007).

In this study we compared three diagnostic assays, bacterial culture, PCR and LAMP in detecting S. zooepidemicus in cultured samples and developed a HRM curve genotyping method which is a post-PCR technique for analysis of DNA sequence variations and could be completed in 20 min.

While bacterial culture and PCR showed high sensitivity (100%) and specificity (100%), LAMP assay produced relatively acceptable sensitivity (89.5%) and equal specificity (100%), when compared with those of PCR with a turn-around time of a 120 min and capable of being suitable to be performed on farm as it requires minimal laboratory equipment. Since the LAMP assay was colorimetric, interpretation of results was also simplified and could be performed without requiring expertise knowledge. However, further improvement of assay sensitivity, possibly by optimising primers sequences so that there are minimal or no mismatches within the primer binding sites, is required before LAMP assay can be used for diagnosis.

The genetic diversity of S. zooepidemicus in equine clinical samples have been investigated using 16 S rRNA (Chanter et al. 1997; Newton et al. 2008; Preziuso et al. 2019), multilocus sequence typing (MLST) (Webb et al. 2008), and whole genome sequencing (Björnsdóttir et al. 2017; Morris et al., 2020). The HRM curve analysis technique which is a post-PCR technique was developed in this study could be used to detect different genotypes and provide results within 20 min. The mathematical model that was employed using a cut-off point method proved to be suitable for bacterial genotyping based on target DNA melting points without visual interpretation of HRM curves.

The PCR-HRM curve analysis developed in this study was capable of detecting S. zooepidemicus in cultured samples with high sensitivity and specificity similar to bacterial culture but in a shorter period of time around six hours. PCR-HRM also differentiated three genotypes in tested samples based on DNA variations within sorD gene which was confirmed with sequencing of PCR amplicons and phylogenetic analysis.

While HRM found three genotypes in tested specimens based on nucleotide variations within this gene, this showed that PCR-HRM curve analysis has the potential to be used for genotyping of S. zooepidemicus isolates. While nucleotide variations are scattered throughout the genome, using different gene(s) containing higher sequence variations among S. zooepidemicus isolates is superior for genotyping purposes. A MLST scheme using seven housekeeping loci has been reported for genotyping of S. zooepidemicus which is widely used (Webb et al. 2008). In addition, the diversity of S. zooepidemicus isolates using whole genome sequencing has been investigated (Björnsdóttir et al. 2017).

The DNA sequence of the 199 nucleotide PCR amplicons showed that distinct differences between conventional and normalised melt curves was as a result of three to seven nucleotide differences within the amplicon sequences. The HRM curve analysis has been successfully used for detection of nucleotide variations including single nucleotide polymorphism and point mutations (Das et al. 2020; Krypuy et al. 2006; Young et al. 2021). Quantity of DNA samples used in PCR can affect the height of HRM curves, therefore it should be noted that equal quantities of DNA can facilitate comparison of HRM curves particularly when large number of samples are tested (Ghorashi et al. 2013). PCR-HRM results can be also affected by poor DNA quality (Wong et al. 2020).

The LAMP assay detected a lower limit of pure DNA prepared from reference strain in the laboratory when compared with PCR, however, failed to detect four S. zooepidemicus in DNA samples extracted from cultured clinical samples. A recent systematic review comparing RT-PCR and RT-LAMP in the diagnosis of COVID-19 showed that LAMP had higher false negative results (12%) than that of RT-PCR (6%) (Pu et al. 2022). The LAMP assay used in this study was a colorimetric assay which results were interpreted by naked-eye as positive (yellow color) or negative (red color). However, some reactions produced a third color (orange) which could not be verified as positive and therefore regarded as negative. Previous studies have reported that an orange color can be observed in positive LAMP reactions that have low DNA load (Aoki et al. 2021). However, in this study, since DNA was quantified using a Nanodrop, and equal quantities of DNA were used in all LAMP reactions, sequence variation within the primer binding sites might have contributed to the false negative results. A systemic review and meta-analysis on accuracies of diagnostic tests has also concluded that quality of samples could potentially influence sensitivity of LAMP assays (Subsoontorn et al. 2020).

Results from this study indicated that LAMP assay can be used to detect S. zooepidemicus in cultured samples collected from stud farms with 91.8% accuracy (95% CI, 0.80–0.98). Despite LAMP showed lower accuracy when compared with PCR (100% accuracy) (95% CI, 0.93-1.00), it provided a better turn-around time. The use of LAMP based assays as viable field-based point of care tests is predicated on the availability of field-based DNA extraction protocols. While some field based extraction procedures have been reported in the literature (Kinoshita et al. 2014; Mason & Botella 2020), their efficacy in conjunction with LAMP assays needs to be investigated. Once effective field extraction methods are available, these LAMP assays offer a viable point-of-care testing alternative compared to other traditional diagnostic assays that are expensive both in terms of time and cost. Further studies comparing qPCR using a probe with LAMP assay would be necessary to evaluate the accuracy of molecular diagnostic tests in detecting S. zooepidemicus particularly on clinical samples.

The PCR-HRM was found to have equal accuracy to the gold standard test (bacterial culture) for detection and potential capacity for genotyping. Both LAMP and PCR-HRM can potentially contribute to the rapid detection of S. zooepidemicus in mare breeding programs and improvement of disease control and animal welfare. However, bacterial culture and antibiotic sensitivity test are helpful in identifying the most effective antibiotic for treatment of clinical cases as well as finding antibiotic-resistant strains.

With the increase in efficiency, the domestic and global equine industry would potentially benefit from reduced testing time resulting in quicker initiation of treatment procedure if required. Subsequently this will improve animal welfare and increase fertility rate within short period of breeding season.

Acknowledgements

The authors wish to thank Ms Lyn Matthews for excellent technical assistance in bacterial culture.

Author contribution

SAG conceived and designed the study. CG performed the experiments. SAG and CG wrote the first draft of the manuscript. SAG, CG, CS and SDP analysed the data and revised the manuscript. All authors read and approved the final manuscript.

Funding

This work was supported by the Graham Centre for Agricultural Innovation under grant number 40825; School of Agricultural, Environmental and Veterinary Sciences under grant number 40702 at Charles Sturt University.

Data availability

Not applicable.

Code availability

Statistics analysis and graphs were made in Rotor-Gene software (Qiagen) version 1.7.27. The ClustalW software, BioEdit Sequence Alignment Editor (version 6.0.9.0) and Molecular Evolutionary Genetics Analysis (MEGA) software were used to analyse sequence data.

Declarations

Animal ethics

Approval for the use of opportunistic samples from mares was granted by the CSU Animal Care and Ethics Committee (Protocol number A19251) and all experiments were performed in accordance with the relevant guidelines and regulations.

Consent to participate

Not applicable. The research did not involve human participants.

Consent for publication

Not applicable. The manuscript does not contain any individual person’s data in any form (including any individual details, images or videos).

Conflict of interest

The authors declare that they have no competing interests.

Footnotes

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Contributor Information

Charlotte Garner, Email: charlottegarner@live.com.

Cyril Stephen, Email: cstephen@csu.edu.au.

Sameer Dinkar Pant, Email: spant@csu.edu.au.

Seyed Ali Ghorashi, Email: aghorashi@csu.edu.au.

References

  1. Aoki MN, De Oliveira Coelho B, Góes LGB, Minoprio P, Durigon EL, Morello LG, Marchini FK, Riediger IN, Do Carmo Debur M, Nakaya HI, Blanes L. Colorimetric RT-LAMP SARS-CoV-2 diagnostic sensitivity relies on color interpretation and viral load. Sci Rep. 2021;11:9026. doi: 10.1038/s41598-021-88506-y. [DOI] [PMC free article] [PubMed] [Google Scholar]
  2. Bannister MF, Benson CE, Sweeney CR. Rapid species identification of group C streptococci isolated from horses. J Clin Microbiol. 1985;21:524–526. doi: 10.1128/jcm.21.4.524-526.1985. [DOI] [PMC free article] [PubMed] [Google Scholar]
  3. Båverud V, Johansson SK, Aspan A. Real-time PCR for detection and differentiation of Streptococcus equi subsp. equi and Streptococcus equi subsp. zooepidemicus. Vet Microbiol. 2007;124:219–229. doi: 10.1016/j.vetmic.2007.04.020. [DOI] [PubMed] [Google Scholar]
  4. Björnsdóttir S, Harris SR, Svansson V, Gunnarsson E, Sigurðardóttir Ó G, Gammeljord K, Steward KF, Newton JR, Robinson C, Charbonneau ARL, Parkhill J, Holden MTG, Waller AS (2017) Genomic dissection of an icelandic epidemic of respiratory disease in horses and associated zoonotic cases. mBio 8. 10.1128/mBio.00826-17 [DOI] [PMC free article] [PubMed]
  5. Bohn AA, Ferris RA, Mccue PM. Comparison of equine endometrial cytology samples collected with uterine swab, uterine brush, and low-volume lavage from healthy mares. Vet Clin Pathol. 2014;43:594–600. doi: 10.1111/vcp.12194. [DOI] [PubMed] [Google Scholar]
  6. Boyle AG, Rankin SC, O’shea K, Stefanovski D, Peng J, Song J, Bau HH. Detection of Streptococcus equi subsp. equi in guttural pouch lavage samples using a loop-mediated isothermal nucleic acid amplification microfluidic device. J Vet Intern Med. 2021;35:1597–1603. doi: 10.1111/jvim.16105. [DOI] [PMC free article] [PubMed] [Google Scholar]
  7. Canisso IF, Segabinazzi LGTM, Fedorka CE. Persistent breeding-induced endometritis in mares - a multifaceted challenge: from clinical aspects to immunopathogenesis and pathobiology. Int J Mol Sci. 2020;21:1432. doi: 10.3390/ijms21041432. [DOI] [PMC free article] [PubMed] [Google Scholar]
  8. Casagrande Proietti P, Bietta A, Coppola G, Felicetti M, Cook RF, Coletti M, Marenzoni ML, Passamonti F. Isolation and characterization of β-haemolytic-streptococci from endometritis in mares. Vet Microbiol. 2011;152:126–130. doi: 10.1016/j.vetmic.2011.04.009. [DOI] [PubMed] [Google Scholar]
  9. Chanter N, Collin N, Holmes N, Binns M, Mumford J. Characterization of the Lancefield group C streptococcus 16S-23S RNA gene intergenic spacer and its potential for identification and sub-specific typing. Epidemiol Infect. 1997;118:125–135. doi: 10.1017/S0950268896007285. [DOI] [PMC free article] [PubMed] [Google Scholar]
  10. Das S, Smith K, Sarker S, Peters A, Adriaanse K, Eden P, Ghorashi SA, Forwood JK, Raidal SR, Repeat spillover of beak and feather disease virus into an endangered parrot highlights the risk associated with endemic pathogen loss in endangered species J Wildl Dis. 2020;56:896–906. doi: 10.7589/2018-06-154. [DOI] [PubMed] [Google Scholar]
  11. Frymus T, Addie DD, Boucraut-Baralon C, Egberink H, Gruffydd-Jones T, Hartmann K, Horzinek MC, Hosie MJ, Lloret A, Lutz H, Marsilio F, Pennisi MG, Radford AD, Thiry E, Truyen U, Möstl K. Streptococcal infections in cats: ABCD guidelines on prevention and management. J Feline Med Surg. 2015;17:620–625. doi: 10.1177/1098612x15588454. [DOI] [PMC free article] [PubMed] [Google Scholar]
  12. Ghorashi SA, Bradbury JM, Ferguson-Noel NM, Noormohammadi AH. Comparison of multiple genes and 16S-23S rRNA intergenic space region for their capacity in high resolution melt curve analysis to differentiate Mycoplasma gallisepticum vaccine strain ts-11 from field strains. Vet Microbiol. 2013;167:440–447. doi: 10.1016/j.vetmic.2013.09.032. [DOI] [PubMed] [Google Scholar]
  13. Ghorashi SA, Noormohammadi AH, Markham PF. Differentiation of Mycoplasma gallisepticum strains using PCR and high-resolution melting curve analysis. Microbiology-Sgm. 2010;156:1019–1029. doi: 10.1099/mic.0.031351-0. [DOI] [PubMed] [Google Scholar]
  14. Holden MT, Heather Z, Paillot R, Steward KF, Webb K, Ainslie F, Jourdan T, Bason NC, Holroyd NE, Mungall K, Quail MA, Sanders M, Simmonds M, Willey D, Brooks K, Aanensen DM, Spratt BG, Jolley KA, Maiden MC, Kehoe M, Chanter N, Bentley SD, Robinson C, Maskell DJ, Parkhill J, Waller AS (2009) Genomic evidence for the evolution of Streptococcus equi: host restriction, increased virulence, and genetic exchange with human pathogens. PLoS Pathog 5:e1000346. 10.1371/journal.ppat.1000346 [DOI] [PMC free article] [PubMed]
  15. Kinoshita Y, Niwa H, Katayama Y (2014) Development of a loop-mediated isothermal amplification method for detecting Streptococcus equi subsp. zooepidemicus and analysis of its use with three simple methods of extracting DNA from equine respiratory tract specimens. J Vet Med Sci 76:1271–1275. 10.1292/jvms.14-0140 [DOI] [PMC free article] [PubMed]
  16. Krypuy M, Newnham GM, Thomas DM, Conron M, Dobrovic A. High resolution melting analysis for the rapid and sensitive detection of mutations in clinical samples: KRAS codon 12 and 13 mutations in non-small cell lung cancer. BMC Cancer. 2006;6:295–295. doi: 10.1186/1471-2407-6-295. [DOI] [PMC free article] [PubMed] [Google Scholar]
  17. Lavoie JP, Fiset L, Laverty S. Review of 40 cases of lung abscesses in foals and adult horses. Equine Vet J. 1994;26:348–352. doi: 10.1111/j.2042-3306.1994.tb04401.x. [DOI] [PubMed] [Google Scholar]
  18. Mason MG, Botella JR. Rapid (30-second), equipment-free purification of nucleic acids using easy-to-make dipsticks. Nat Protoc. 2020;15:3663–3677. doi: 10.1038/s41596-020-0392-7. [DOI] [PMC free article] [PubMed] [Google Scholar]
  19. Morris ERA, Hillhouse AE, Konganti K, Wu J, Lawhon SD, Bordin AI, Cohen ND. Comparison of whole genome sequences of Streptococcus equi subsp. equi from an outbreak in Texas with isolates from within the region, Kentucky, USA, and other countries. Vet Microbiol. 2020;243:108638. doi: 10.1016/j.vetmic.2020.108638. [DOI] [PubMed] [Google Scholar]
  20. Newton J, Laxton R, Wood J, Chanter N. Molecular epidemiology of Streptococcus zooepidemicus infection in naturally occurring equine respiratory disease. Vet J. 2008;175:338–345. doi: 10.1016/j.tvjl.2007.02.018. [DOI] [PubMed] [Google Scholar]
  21. Nocera FP, Papulino C, Del Prete C, Palumbo V, Pasolini MP, De Martino L. Endometritis associated with Enterococcus casseliflavus in a mare: a case report. Asian Pac J Trop Biomed. 2017;7:760–762. doi: 10.1016/j.apjtb.2017.07.016. [DOI] [Google Scholar]
  22. Noll LW, Stoy CPA, Wang Y, Porter EG, Lu N, Liu X, Burklund A, Peddireddi L, Hanzlicek G, Henningson J, Chengappa MM, Bai J. Development of a nested PCR assay for detection of Streptococcus equi subspecies equi in clinical equine specimens and comparison with a qPCR assay. J Microbiol Methods. 2020;172:105887. doi: 10.1016/j.mimet.2020.105887. [DOI] [PubMed] [Google Scholar]
  23. North SE, Wakeley PR, Mayo N, Mayers J, Sawyer J. Development of a real-time PCR to detect Streptococcus equi subspecies equi. Equine Vet J. 2014;46:56–59. doi: 10.1111/evj.12088. [DOI] [PubMed] [Google Scholar]
  24. Pasolini MP, Prete CD, Fabbri S, Auletta L (2016) Endometritis and infertility in the mare – the challenge in equine breeding industry–a review. In: Darwish AM (ed) Genital Infections and Infertility. IntechOpen. 10.5772/62461
  25. Preziuso S, Moriconi M, Cuteri V (2019) Genetic diversity of Streptococcus equi subsp. zooepidemicus isolated from horses. Comp Immunol Microbiol Infect Dis 65:7–13. 10.1016/j.cimid.2019.03.012 [DOI] [PubMed]
  26. Priestnall S, Erles K. Streptococcus zooepidemicus: an emerging canine pathogen. Vet J. 2011;188:142–148. doi: 10.1016/j.tvjl.2010.04.028. [DOI] [PMC free article] [PubMed] [Google Scholar]
  27. Pu R, Liu S, Ren X, Shi D, Ba Y, Huo Y, Zhang W, Ma L, Liu Y, Yang Y, Cheng N. The screening value of RT-LAMP and RT-PCR in the diagnosis of COVID-19: systematic review and meta-analysis. J Virol Methods. 2022;300:114392. doi: 10.1016/j.jviromet.2021.114392. [DOI] [PMC free article] [PubMed] [Google Scholar]
  28. Rasmussen CD, Haugaard MM, Petersen MR, Nielsen JM, Pedersen HG, Bojesen AM (2013) Streptococcus equi subsp. zooepidemicus isolates from equine infectious endometritis belong to a distinct genetic group. Vet Res 44:26–26. 10.1186/1297-9716-44-26 [DOI] [PMC free article] [PubMed]
  29. Silva MSE, Costa MMD, De Avila Botton S, Barretta C, Groff ACM, De Vargas AC. Phenotypical assays and partial sequencing of the hsp60 gene for identification of Streptococcus equi. Curr Microbiol. 2007;54:331–334. doi: 10.1007/s00284-005-0458-3. [DOI] [PubMed] [Google Scholar]
  30. Soedarmanto I, Pasaribu FH, Wibawan IW, Lämmler C. Identification and molecular characterization of serological group C streptococci isolated from diseased pigs and monkeys in Indonesia. J Clin Microbiol. 1996;34:2201–2204. doi: 10.1128/jcm.34.9.2201-2204.1996. [DOI] [PMC free article] [PubMed] [Google Scholar]
  31. Subsoontorn P, Lohitnavy M, Kongkaew C. The diagnostic accuracy of isothermal nucleic acid point-of-care tests for human coronaviruses: a systematic review and meta-analysis. Sci Rep. 2020;10:22349. doi: 10.1038/s41598-020-79237-7. [DOI] [PMC free article] [PubMed] [Google Scholar]
  32. Thompson JD, Higgins DG, Gibson TJ. CLUSTAL W: improving the sensitivity of progressive multiple sequence alignment through sequence weighting, position-specific gap penalties and weight matrix choice. Nucleic Acids Res. 1994;22:4673–4680. doi: 10.1093/nar/22.22.4673. [DOI] [PMC free article] [PubMed] [Google Scholar]
  33. Webb K, Jolley KA, Mitchell Z, Robinson C, Newton JR, Maiden MC, Waller A. Development of an unambiguous and discriminatory multilocus sequence typing scheme for the Streptococcus zooepidemicus group. Microbiology. 2008;154:3016–3024. doi: 10.1099/mic.0.2008/018911-0. [DOI] [PubMed] [Google Scholar]
  34. Wong SA, Woodgate RG, Pant SD, Ghorashi SA. Rapid detection of Bovicola ovis using colourimetric loop-mediated isothermal amplification (LAMP): a potential tool for the detection of sheep lice infestation on farm. Parasitol Res. 2020;119:395–401. doi: 10.1007/s00436-019-06552-y. [DOI] [PubMed] [Google Scholar]
  35. Young P, Tarce P, Adhikary S, Connolly J, Crawshaw T, Ghorashi SA. Evaluation of high-resolution melt curve analysis for rapid differentiation of Campylobacter hepaticus from other species in birds. PLoS ONE. 2021;16:e0251328. doi: 10.1371/journal.pone.0251328. [DOI] [PMC free article] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Availability Statement

Not applicable.

Statistics analysis and graphs were made in Rotor-Gene software (Qiagen) version 1.7.27. The ClustalW software, BioEdit Sequence Alignment Editor (version 6.0.9.0) and Molecular Evolutionary Genetics Analysis (MEGA) software were used to analyse sequence data.

Articles from Veterinary Research Communications are provided here courtesy of Nature Publishing Group

RESOURCES