Introduction

Mycoplasma gallisepticum (MG) remains one of the most important bacterial pathogens worldwide, causing a respiratory disease called chronic respiratory disease (CRD) in infected poultry flocks and resulting in monetary losses for treatment and control1. MG has both horizontal and vertical transmission. MG infection can cause a high feed conversion ratio, egg production loss, poor hatchability, and carcass degradation1. Stipkovits and Kempf2 investigated the economic loss from MG and found a 10–20% drop in egg production in infected layers and a body weight loss of 10–20% in infected broilers. In Thailand, approximately 25% of all laying hens in the poultry industry are infected with MG, leading to a loss of approximately 15 million U.S. dollars due to a decrease in egg production3.

Due to this widespread MG infection, vaccination is an important preventive strategy generally used in the Thailand poultry industry. Live vaccine strains, including the F, ts-11, and 6/85 strains, and inactivated MG vaccines have been used for years1. In particular, the F strain is one of the most effective vaccine strains and is widely used in Thailand. Therefore, a technique to differentiate between vaccine and field MG strains in flocks with suspected MG infection is needed. Several studies have investigated techniques for MG classification4,5,6,7,8,9. For example, gene targeted sequencing (GTS) analysis was developed by Ferguson et al.4 This technique has been used to determine the gene sequences of partial surface proteins of MG, including the gapA, mgc2, pvpA and MGA_0319 genes. The multilocus sequence typing scheme (MLST) is a technique that many studies have used and is regarded as the gold standard for bacterial typing6,10,11. This technique uses MG housekeeping genes for molecular identification, which is an effective way to determine the relationship between MG strains. Both GTS and MLST have been widely used to monitor and characterize MG strains6. Additionally, the whole genome sequence (WGS) can be used to analyse the entire genomic sequence of MG12,13. High-resolution melt (HRM) curve analysis is another new molecular technique that classifies MG strains by using the vlhA, pvpA, gapA, and mgc2 genes as well as the 16S-23S rRNA intergenic space region (IGSR) with conventional and real-time PCR8,9. The most commonly used technique in Thailand is random amplification of polymorphic DNA (RAPD). However, RAPD has low reproducibility, and results from different laboratories cannot be compared14,15. Sequencing is a potential technique for MG classification. MG strains can be differentiated with partial DNA sequences and compared among laboratories in different areas or countries4,16,17. In addition, gene targeted sequencing (GTS) is a cost-efficient and affordable method for use in developing countries, including Thailand, where advanced techniques are not generally feasible.

The important genes of MG, including gapA, mgc2, pvpA and MGA_0319 (lp), have been investigated in several epidemiological studies4,18,19. In Thailand, Limsatanun et al.20 classified MG strains with partial mgc2 gene sequences; thus, the partial mgc2 gene can be used to classify Thai MG strains from vaccine strains and various strains from different countries. However, partial mgc2 gene classification is not a reliable method for MG characterization4.

The aim of this study was to determine a GTS technique for differentiating field and vaccine MG strains in commercial chicken flocks from different regions in Thailand. This is the first study to use 4 partial MG gene sequences for commercial MG classification in Thailand.

Results

PCR amplification

All twenty-four Thai MG isolates were detected by MG-specific PCR amplification following the Lauerman method21. To amplify partial mgc2 genes, which were 615 bp in size, 22 Thai MG isolates were successfully amplified and sequenced. According to the specific partial gapA PCR with 306 bp, 21 Thai MG isolates were positive and included in the phylogenetic analysis, while 20 samples of Thai MG isolates were successfully amplified using the pvpA and MGA_0319 (lp) primers with lengths of 456 and 495 bp, respectively. All nucleotide sequences from Thai MG isolates in this study were submitted to GenBank and given accession numbers (Table 1).

Table 1 MG PCR Primers for MG characterization.
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Phylogenetic analysis

The phylogenetic tree based on the partial mgc2 gene demonstrated that 3 Thai MG isolates were closely related to the F strain. AHRU/2014/CU4508.1 was grouped together with the F strain, while AHRU/2020/CU0143.1 and AHRU/2020/0147.1 showed 97.6% genetic similarity to the F strain (Fig. 1). According to the phylogenetic tree based on the partial gapA gene, AHRU/2014/CU4508.1 showed 99.5% genetic similarity to the F strain. AHRU/2020/CU3704.1 was also grouped with the F strain (Fig. 2). The phylogenetic analysis of the partial pvpA gene placed all Thai MG isolates in the same cluster except the reference strain S6 (Fig. 3). Four Thai MG isolates showed 94.3% genetic similarity to the 6/85 strain. AHRU/2014/CU450 8.1 was grouped with the F strain with 100% similarity. The partial lp gene sequences of Thai MG were compared with reference strains. The 6/85 strain was grouped into different Clusters. AHRU/2014/CU4508.1 and AHRU/2020/CU0143.1 had 100% genetic similarity to the F strain and 99.2% genetic similarity to the ts-11 strain (Fig. 4). The genetic similarity of Thai MG strains and F strain is shown in Table 2. The lp gene showed the highest similarity of genetic sequences (98.2–100%) between the F strain and Thai MG strains. The phylogenetic trees with DNA sequence data are available in the Supplementary Information.

Figure 1
figure 1

A phylogenetic tree of Thai MG and reference strains based on the alignment of the partial mgc2 gene was constructed with the unweighted pair group method with arithmetic mean (UPGMA) using Bionumeric version 7.6 software.

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Figure 2
figure 2

A phylogenetic tree of Thai MG and reference strains based on the alignment of the partial gapA gene was constructed with the unweighted pair group method with arithmetic mean (UPGMA) using Bionumeric version 7.6 software.

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Figure 3
figure 3

A phylogenetic tree of Thai MG and reference strains based on the alignment of the partial pvpA gene was constructed with the unweighted pair group method with arithmetic mean (UPGMA) using Bionumeric version 7.6 software.

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Figure 4
figure 4

A phylogenetic tree of Thai MG and reference strains based on the alignment of the partial pvpA gene was constructed with the unweighted pair group method with arithmetic mean (UPGMA) using Bionumeric version 7.6 software.

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Table 2 The genetic similarity (%) between the F strain and Thai MG isolates (Estimated from the number of base substitutions using the maximum composite likelihood model).
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Discussion

Avian mycoplasmosis is an important disease-causing pathogen in the poultry industry with substantial economic impacts. Live, inactivated, and recombinant MG vaccines have been used in Thailand for a long time. Due to the increased use of MG vaccines, differentiation between field and vaccine strains is needed. Molecular characterization of MG has been investigated in many countries4,5,7,22,23. This study is the first to use the GTS technique on Thai MG strains with 4 partial MG gene sequences. The partial mgc gene has been used for MG characterization in many epidemiological studies6,20,24. It encodes the MGC2 protein, which coordinates with the gapA gene-encoded protein for cell attachment25 and is involved in MG immunogenicity12,26.

In a previous study, Armour et al.22 investigated MG isolates from South Africa using intergenic spacer regions (IGSRs), mgc2 and gapA genes. Thirty-six MG isolates were classified into 8 types by the mgc2 gene and 2 types by the gapA gene. Thus, the mgc2 gene had a higher discriminatory power than the gapA gene. Another study in Russia conducted an epidemiological investigation of MG7. The results showed that mgc2 gene had good discriminatory power, while gapA did not provide a good discriminatory index for MG classification. However, the use of only a single gene for classification could not determine the similarity between MG isolates. Additionally, some MG isolates were negative for the mgc2 gene according to the PCR assay, resulting in a failure to obtain mgc2 sequences5,6,19,22; thus, using only one partial gene sequence is insufficient to characterize MG.

In the present study, the lp gene of Thai MG isolates was more conserved than the gapA, mgc2 and pvpA genes, as 18 out of 20 Thai MG isolates showed 100% genetic similarity on this gene. The use of partial gapA showed the highest genetic variation among Thai isolates. These results contradicted those of previous studies4,7,22, which indicated that MG isolates from the same area would have lower genetic diversity than MG isolates from different regions22. In the present study, Thai MG isolates were identified with 4 genes using the phylogenetic tree (UPMGA) method. AHRU/2014/CU4508.1 had the closest genetic relationship to the F strain. The UPMGA results showed that AHRU/2014/CU4508.1 was grouped with the F strain on all 4 partial gene analyses. Interestingly, all Thai MG isolates in this study were collected from farms with unvaccinated flocks. In Thailand, poultry breeders and layers are widely vaccinated with the F strain. Interestingly, the AHRU/2014/CU4508.1 isolate from these farms might have been contaminated from other farms with vaccinated flocks. The F strain from the live MG vaccine can be transmitted both horizontally and vertically27,28,29. Furthermore, several epidemiological studies have shown that the F strain can cause MG outbreaks if it spreads from vaccinated to nonvaccinated flocks5,24,30. Other Thai MG isolates in this study varied in genetic classification depending on the gene analysed. The results of gapA and mgc2 gene analysis showed that AHRU/2003/CU5113.2 and AHRU/2003/CU5808.2 were grouped with the S6 strain with 97% and 99.4% genetic similarity, respectively. In contrast, using the partial pvpA gene sequence indicated that the S6 strain was separated from all Thai MG isolates, including AHRU/2003/CU5113.2 and AHRU/2003/CU5808.2. These results indicated that AHRU/2003/CU5113.2 and AHRU/2003/CU5808.2 might be genetically related to the S6 strain. DNA sequences of all 4 virulence genes could not be obtained for some Thai MG isolates. For example, the Thai MG isolate AHRU/2009/CU3704 could only be classified by phylogenetic analysis of gapA and pvpA genes because it was negative for mgc2 and pvpA according to the PCR analysis. Plausibly, this lack of detection could be because of the poor quality of DNA due to the presence of multiple strains in the broth medium sample and/or genetic mutations between and within MG strains6,31,32.

In conclusion, the Thai MG isolates in this study could be differentiated with partial MG genes, including the gapA, mgc2, pvpA and MGA_0319 (lp) genes. All Thai MG isolates could be classified with at least 2 out of 4 partial gene sequences, especially the partial gapA and mgc2 genes, which had satisfactory discriminatory power for Thai MG characterization. Using partial DNA sequencing for MG characterization is an effective and reproducible method for establishing the genetic relationship between MG strains and differentiating between vaccine and field strains. In addition, this study was the first epidemiological study of Thai MG strains to use 4 partial MG gene sequences, demonstrating the genetic diversity of circulating MG strains in Thailand. In future studies, the GTS technique should be implemented along with other molecular techniques, including a multilocus sequence typing scheme, to provide more epidemiological and evolutionary data and improve the system for monitoring MG outbreaks in poultry farms in Thailand.

Materials and methods

MG isolates

Twenty-four Thai MG isolates were used in this study. All isolates were collected during 2003–2020 by Prof. Somsak Pakpinyo, Department of Veterinary Medicine, Faculty of Veterinary Science, Chulalongkorn University. All MG isolates were collected from choanal cleft of dead chicken and were propagated in FMS medium supplemented with 15% swine serum following previously reported methods33 and incubated at 37 °C until the broth colour changed from pink to orange. All isolates were confirmed as MG by polymerase chain reaction (PCR) assay21.

Molecular typing

The DNA from each Thai MG isolate was extracted with an equal volume of phosphate buffered saline (PBS) and then amplified by PCR. The primers in this study were designed by Ferguson4 (Table 3). A PCR assay was performed to detect the partial gapA, pvpA, MGA_0319 and mgc2 genes. The PCR mixture consisted of 500 mM KCl, 100 mM Tris–HCl (pH 8.3), 1.25 mM MgCl2, 1 mM dNTP (Thermo Scientific, Vilnius, Lithuania), 10 pmol each of primer (Qiagen®, Valencia, CA, USA), 1.25 µl of Taq polymerase (Promega, Madison, WI, USA) and 2.5 µl (125 ng) of the DNA template. The amplification reaction was performed in a DNA thermal cycler at 94 °C for 3 min, followed by 40 cycles of 94 °C for 20 s, 55–60 °C for 40 s, 72 °C for 60 s, and 72 °C for 5 min for the gapA, pvpA, MGA_0319 (lp) and mgc2 genes. The PCR products were 332, 702, 590 and 824 bp, respectively4.

Table 3 Thai MG strains and GenBank accession numbers.
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Reference sequences

Four reference strains were used in this study. The F strain was the vaccine strain provided by a local distributor (MSD, Thailand). The S6 strain was obtained from ATCC (15302). The ts-11 and 6/85 strain sequences were obtained from Prof. Somsak Pakpinyo, Department of Veterinary Medicine, Faculty of Veterinary Science, Chulalongkorn University.

DNA sequence analysis

Amplified PCR products of MG-targeted gene-positive extracts were submitted to determine the sequence. Partial mgc2 gene sequences (Accession Numbers KX268616–KX268632) from 16 Thai MG isolates had been submitted to GenBank in a previous study20 (Table 3.) All sequences were analysed with the Editseq program (Lasergene, DNASTAR Inc., USA), and a consensus was constructed with the Seqman program (Lasergene, DNASTAR Inc., USA). Thai MG isolates and reference gene sequence data were aligned to construct a phylogenetic tree in Bionumeric version 7.6 software (Applied Maths, Sint-Martens-Latem, Belgium). Cluster analysis was performed with the UPGMA method. The similarity coefficients of Thai MG isolates and reference strains were determined from multiple sequence alignments.