Skip to main content
  • Research note
  • Open access
  • Published:

Discrimination between some Mycoplasma spp. and Acholeplasma laidlawii in bovine milk using high resolution melting curve analysis

This article has been updated

Abstract

Objectives

This study aimed to provide a rapid, accurate and cost-effective diagnostic real time polymerase chain reaction-high resolution melting curve assay (PCR-HRM) to identify and distinguish between four different mycoplasmas and Acholeplasma laidlawii isolated at cow-level from a single commercial dairy farm in South Australia. One set of genus-level universal primers was designed targeting the 16S ribosomal RNA gene.

Results

Real time PCR-HRM analysis was able to identify and distinguish between five different mollicutes, namely A. laidlawii, M. arginini, M. bovirhinis, M. bovis and uncultured Mycoplasma. Results were confirmed through sequencing. Our developed assay provides rapid and accurate screening for Mycoplasma mastitis detection.

Introduction

Mycoplasma mastitis is of emerging significance worldwide, posing significant economic impacts on the dairy industry. Early detection of Mycoplasma mastitis is important to disease control strategies [1]. Several Mycoplasma spp. are mainly responsible for mastitis, including M. bovis, M. bovoculi, M. alkalescence, M. alvi, M. bovigenetalium, M. bovirhinis, Mycoplasma species bovine group 7, M. californicum, M. dispar, M. canis, M. verecundum, M. canadense and M. mycoides subsp. mycoides [2]. Acholeplasma spp. may be isolated from milk either as a contaminant [3] or as a co-invader with other mycoplasmas [4, 5]. Conventional microbial culture of mollicutes can be laborious and time-consuming with a variety of species-specific growth requirements [6]. Misdiagnosis of Mycoplasma using serological detection is common due to the lag period required for antibody formation. Therefore, a rapid and accurate diagnostic assay is required for screening of mycoplasma in dairy herds. High resolution melting curve analysis (HRM) has been recently developed and widely used for phenotyping at strain or species-level of various organisms including mycoplasmas [7, 8]. However, field isolates of mastitis related mycoplasmas and other milk environmental mollicutes have not been assessed previously using this method.

The aim of this study was to provide a suitable diagnostic real time polymerase chain reaction-high resolution melting curve analysis (PCR-HRM) to identify and distinguish between five different mollicutes isolated at cow-level from a single commercial dairy farms in South Australia.

Main text

Methods

Samples were selected based on conventional PCR findings of a previous study conducted on single commercial dairy farm in South Australia. This farm had a history of repeated mastitis treatment failure with high somatic cell count (SCC) and poor response to antimicrobials [4]. Six isolates for each of the following species were selected in this study: A. laidlawii, M. arginini, M. bovirhinis, M. bovis and uncultured mollicutes. One set of genus-level universal primers targeting the 16S rRNA gene was designed for real time-PCR. Forward primer Mol-F: GGCGAAYGGGTGAGTAACAC and reverse primer Mol-R: CATHGYCTTGGTRRGCYNTTA. The real time PCR mixture was prepared using HRM kit AccuMelt HRM SuperMix (Quantabio, Australia). DNA amplification was conducted in a 96 microplate (Illumina, San Diego, CA, USA). Each well contained 10 µL reaction solution of 5 µL HRM SuperMix, 1 µL DNA template (approximately 20 ng), 1 µL each primer (0.2 nmol) and 2 µL nuclease free water (Qiagen, Germany). The reaction was conducted using an Illumina Thermal Cycler with pre-heating activation for 2 min followed by 40 PCR cycles of three steps: denaturation at 95 °C for 15 s, annealing at 60 °C for 45 s, then extension at 72 °C for 15 s. HRM was performed at 55–95 °C at the rate of 0.1 °C. Results were analysed via EcoStudy software (version 5.0, Illumina). PCR products were subject to electrophoresis in 1.5% agarose gels and visualised by staining with Gel Red. PCR products from the 16S rRNA gene were submitted to the Australian Genome Research Facility Ltd (AGRF, Adelaide, South Australia) for Sanger sequencing. Each fragment was sequenced in forward and reverse directions. To reconstitute the sequence, forward and reverse sequences were edited and assembled using BioEdit package v.7.0.4.1. Edited sequences were blasted against existing sequences in GeneBank using the basic local alignment search tool (BLAST) (http://blast.ncbi.nlm.nih.gov/Blast.cgi) and nucleotide sequences from relevant Mycoplasma strains were used as reference strains for nucleotide alignments using ClustalW program version 2.

Results

Five different mollicutes, A. laidlawii, M. arginini, M. bovirhinis, M. bovis and uncultured mollicutes, produced normalised and derivative melt curves (Fig. 1). A. laidlawii (Accession No. LC201977.1) generated one melting peak at 81.2 °C, M. arginini (Accession No. LC158832.1) generated two melting peaks at 88.5 and 84.7 °C. M. bovirhinis (Accession No. AP018135.1) generated three melting peaks at 85.7, 77.6 and 88.2 °C. M. bovis (Accession No. KX462439.1) generated two melting peaks at 77.6 and 85.2 °C. Uncultured Mycoplasma spp. (Accession No. LT679634.1) generated one melting peak at 83.9 °C.

Fig. 1
figure 1

Normalised and different high resolution melting curves generated by EcoStudy software of five different mollicutes isolated from bovine milk: purple—Acholeplasma laidlawii, green—Mycoplasma arginini, blue—M. bovirhinis, yellow—M. bovis, red—uncultured Mycoplasma spp.

Discussion

While conventional culture, the traditional method for mollicute detection, imposes technical challenges in distinguishing between milk pathogenic and saprophytic mollicutes, our study indicated that real time PCR-HRM assay provides a sensitive, rapid and cost-effective screening method to identify and discriminate between some pathogenic and environmental mollicutes isolated from milk DNA. Effects of some of these mollicutes on SCC and milk composition have been previously studied [4]. We considered SCC as the crucial factor that discriminates between contagious and environmental mollicutes. M. bovis was widely reported as a main mastitis causing Mycoplasma [9, 10]. Inconsistent results have been reported regarding involvement of M. arginini, M. bovirhinis and A. laidlawii in bovine mastitis, particularly with co-infection Mycoplasma mastitis [5, 11, 12]. However, several studies indicate these mollicutes are not significant pathogens [3, 13].

Melting profile, introduced in 2002, is widely used for genotyping a wide range of microorganisms [14,15,16,17]. HRM-based assay describes correlation between temperature and DNA extent of denaturation [18]. The variety of melting temperatures for different species is attributed to DNA length, sequencing and GC content [14]. In summary, as an alternative to sequencing, our developed real time PCR-HRM assay offered a rapid, low-cost and simple discriminative method to distinguish between some mastitis causing pathogenic mycoplasmas and other saprophytic mollicutes in bovine milk. This method was useful for screening of Mycoplasma mastitis and can be extended to identify more mollicutes species.

Limitations

One of the limitations of HRM-based analysis in Mycoplasma mastitis detection is the inability to detect co-infection cases due to amplimer concentration differences and the requirement of separation each individual amplicon Tm [18]. Primers used in this study were designed to target more spp. of major Mycoplasma-causing mastitis in dairy herds. However, in this study, we used only field isolates of five different mollicutes.

Change history

  • 13 September 2021

    The original article was updated to amend author Razi Jozani’s affiliation.

Abbreviations

HRM:

high resolution melt

PCR:

polymerase chain reaction

SCC:

somatic cell count

References

  1. Kirk JH, Lauerman LH, Roberts C. Mycoplasma mastitis in dairy cows. Compend Contin Educ Pract Vet. 1994;16(4):541–52.

    Google Scholar 

  2. Nicholas R, Ayling R, McAuliffe L. Mycoplasma mastitis. Vet Rec. 2007;160(11):382 (author reply 383).

    Article  Google Scholar 

  3. Boonyayatra S, Fox LK, Gay JM, Sawant A, Besser TE. Discrimination between Mycoplasma and Acholeplasma species of bovine origin using digitonin disc diffusion assay, nisin disc diffusion assay, and conventional polymerase chain reaction. J Vet Diagn Investig. 2012;24(1):7–13.

    Article  Google Scholar 

  4. Al-Farha AAB, Hemmatzadeh F, Khazandi M, Hoare A, Petrovski K. Evaluation of effects of Mycoplasma mastitis on milk composition in dairy cattle from South Australia. BMC Vet Res. 2017;13(1):351.

    Article  Google Scholar 

  5. Counter DE. A severe outbreak of bovine mastitis associated with Mycoplasma bovigenitalium and Acholeplasma laidlawii. Vet Rec. 1978;103(7):130–1.

    Article  CAS  Google Scholar 

  6. Hahn RG, Kenny GE. Differences in arginine requirement for growth among arginine-utilizing Mycoplasma species. J Bacteriol. 1974;117(2):611–8.

    Article  CAS  Google Scholar 

  7. Ghorashi SA, Noormohammadi AH, Markham PF. Differentiation of Mycoplasma gallisepticum strains using PCR and high-resolution melting curve analysis. Microbiology. 2010;156(Pt 4):1019–29.

    Article  CAS  Google Scholar 

  8. Rebelo AR, Parker L, Cai HY. Use of high-resolution melting curve analysis to identify Mycoplasma species commonly isolated from ruminant, avian, and canine samples. J Vet Diagn Investig. 2011;23(5):932–6.

    Article  Google Scholar 

  9. Aebi M, van den Borne BH, Raemy A, Steiner A, Pilo P, Bodmer M. Mycoplasma bovis infections in Swiss dairy cattle: a clinical investigation. Acta Vet Scand. 2015;57:10.

    Article  Google Scholar 

  10. Kunkel JR. Isolation of Mycoplasma bovis from bulk milk. Cornell Vet. 1985;75(3):398–400.

    CAS  PubMed  Google Scholar 

  11. Szacawa E, Niemczuk K, Dudek K, Bednarek D, Rosales R, Ayling R. Mycoplasma bovis infections and co-infections with other Mycoplasma spp. with different clinical manifestations in affected cattle herds in eastern region of Poland. Bull Vet Inst Pulawy. 2015;59(3):331–8.

    Article  Google Scholar 

  12. González RN, Wilson DJ. Mycoplasmal mastitis in dairy herds. Vet Clin N Am Food Anim Pract. 2003;19(1):199–221.

    Article  Google Scholar 

  13. Jasper D, Dellinger J, Rollins M, Hakanson H. Prevalence of mycoplasmal bovine mastitis in California. Am J Vet Res. 1979;40(7):1043–7.

    CAS  PubMed  Google Scholar 

  14. Reed GH, Kent JO, Wittwer CT. High-resolution DNA melting analysis for simple and efficient molecular diagnostics. Pharmacogenomics. 2007;8(6):597.

    Article  CAS  Google Scholar 

  15. Ren X, Fu Y, Xu C, Feng Z, Li M, Zhang L, Zhang J, Liao M. High resolution melting (HRM) analysis as a new tool for rapid identification of Salmonella enterica serovar Gallinarum biovars Pullorum and Gallinarum. Poult Sci. 2017;96(5):1088–93.

    Article  CAS  Google Scholar 

  16. Yong TB, Hashim R, Noor AM, Hamzah SH, Ahmad N. Identification of Brucella spp. isolated from human brucellosis in Malaysia using high-resolution melt (HRM) analysis. Diagn Microbiol Infect Dis. 2015;81(4):227–33.

    Article  Google Scholar 

  17. Gago S, Zaragoza Ó, Cuesta I, Rodríguez-Tudela JL, Cuenca-Estrella M, Buitrago MJ. High-resolution melting analysis for identification of the Cryptococcus neoformans–Cryptococcus gattii complex. J Clin Microbiol. 2011;49(10):3663–6.

    Article  CAS  Google Scholar 

  18. Tong SY, Giffard PM. Microbiological applications of high-resolution melting analysis. J Clin Microbiol. 2012;50(11):3418–21.

    Article  CAS  Google Scholar 

Download references

Authors’ contributions

AAA, FH and KP participated in the study design and coordination. AAA, KP and AH contributed to sample collection. AAA and FH contributed in sample processing and real time PCR in the PC2 laboratory. RJ designed the primers for HRM analysis All authors were involved in drafting the manuscript, corrected. All authors read and approved the final manuscript.

Acknowledgements

The authors would like to express their special thanks to the farmer and farm staff for their cooperation and interest in the study.

Competing interests

The authors declare that they have no competing interests.

Availability of data and materials

The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.

Consent to publish

Not applicable.

Ethics approval and consent to participate

Not applicable. Samples were collected by field veterinary support as a part of the mastitis investigation as per farmer request and no Animal Ethics application was required (Australian code for the care and use of animals for scientific purposes, 8th edition, 2013).

Funding

The first author was partially funded by The Higher Committee for Education Development in Iraq in form of a scholarship. All field and laboratory procedures were financially supported by the University of Adelaide.

Publisher’s Note

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

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Abd Al-Bar Al-Farha.

Rights and permissions

Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Al-Farha, A.AB., Petrovski, K., Jozani, R. et al. Discrimination between some Mycoplasma spp. and Acholeplasma laidlawii in bovine milk using high resolution melting curve analysis. BMC Res Notes 11, 107 (2018). https://0-doi-org.brum.beds.ac.uk/10.1186/s13104-018-3223-y

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://0-doi-org.brum.beds.ac.uk/10.1186/s13104-018-3223-y

Keywords