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The Characterization and Differentiation of Recombinant Lumpy Skin Disease Isolates Using a Region within ORF134

1
Federal Center for Animal Health, 600901 Vladimir, Russia
2
Agricultural Research Council-Onderstepoort Veterinary Institute, 100 Old Soutpan Road, Onderstepoort 0110, South Africa
3
Department of Biotechnology, University of the Western Cape, Robert Sobukwe Road, Bellville 7535, South Africa
*
Author to whom correspondence should be addressed.
Appl. Microbiol. 2023, 3(1), 35-44; https://doi.org/10.3390/applmicrobiol3010003
Submission received: 5 November 2022 / Revised: 10 December 2022 / Accepted: 26 December 2022 / Published: 29 December 2022

Abstract

:
The recent description and characterization of several novel and unique lumpy skin disease virus (LSDV) strains have revealed the inadequacy of current techniques for differentiating between vaccine- and wild-type viruses. The lack of reliable sequencing targets for promptly distinguishing circulating recombinant vaccine-like strains (RVLSs) highlights the need to develop a single and simple differentiation tool. In this study, we analyzed the available LSDV whole-genome sequences and identified a 705-bp region in open reading frame (ORF) LW134. Based on a single run of nucleotide sequencing and phylogenetic analysis, the region with 13 informative single nucleotide polymorphisms (SNPs) was capable of accurately segregating the novel RVLSs into the same five clusters previously confirmed by whole-genome sequencing. In addition, archived RVLSs from Russia were analyzed for further characterization using the newly described single PCR and sequencing assay. The ORF LW134 assay identified one archived RVLS as a novel cluster distinct from the previously described five clusters, while clustering the remaining samples into previously designated lineages, demonstrating the reliability of the assay. The novel PCR and sequencing assays described in this study have great potential for accurately delineating the molecular and evolutionary affiliation of circulating RVLSs.

1. Introduction

Capripoxviruses are emerging pathogens that threaten the global livestock industry [1]. Because of the considerable economic losses to commercial farms and rural communities caused by a lumpy skin disease virus (LSDV) outbreak, these capripoxvirus infections have been designated as notifiable to the World Organization for Animal Health [2]. The aetiological agents are known as LSDV, which belongs to the genus capripoxvirus in the family poxviridae. It primarily affects cattle and water buffaloes, while sheeppox virus and goatpox virus affect sheep and goats, respectively [3]. The LSDV genome is a linear double-stranded DNA with approximately 151 kilobase pairs (Kbps) and 156 open reading frames (ORFs), each of which consists of a central coding region flanked by identical 2.4 kbp-inverted terminal repeat regions [4].
Typical clinical symptoms include the development of skin lumps five to seven days after infection, followed by necrosis and crust sloughing. The open nodules can act as routes for viral shedding and bacterial infection [1,5,6]. Excreted fluids from nasal cavities and skin lesions, which contain high concentrations of the virus, are attractive to flies and other insects, resulting in insect-mediated disease transmission [7,8]. LSDV poses a serious economic risk not only to the global cattle industry but also to wildlife, as disease outbreaks have been reported in water buffaloes and game animals, particularly antelopes in sub-Saharan Africa [9,10,11].
Since the first report of lumpy skin disease (LSD) in Zambia in the 1920s, the disease has been maintained and confined to the African continent for the remainder of the 20th century [12]. However, during this century, it has spread across the Middle East, Turkey, and Azerbaijan, reaching the European Union, the Balkans, Russia, and Kazakhstan, with recent outbreaks in south Asia, including China, Vietnam, Thailand, India, Bangladesh, and Nepal [13,14,15,16,17].
Prior to 2017, LSDVs isolated during active outbreaks could be divided into two clusters (1.1 and 1.2) based on their whole-genome sequences [18,19,20]. This dramatically changed with the first description of a novel LSDV recombinant strain isolated during an active outbreak in Saratov, Russia, in 2017 [21]. Since the description of Saratov/Russia/2017 (Cluster 2.1), four additional novel recombinants have been described, the first two in Udmurtiya (Cluster 2.2) and Tyumen (Cluster 2.4) in Russia in 2019, the third in Kazakhstan (Cluster 2.3) in 2018, and the last in China (Cluster 2.5) in 2019 [22,23,24]. Phylogenomic clustering of the available complete LSDV genomes indicates the novel recombinant vaccine-like LSDV strains (RVLSs) were derived from two parental live attenuated vaccine (LAV) strains, Neethling-LW1959 or any other Neethling vaccine strain, and the vaccine Kenyan Sheep and Goat Pox-Ovine (KSGP-O240) [20]. The lineage first described in China in 2019 (Cluster 2.5) is currently the dominant virus circulating in Southeast Asia [24,25,26,27,28].
The continued spread of RVLSs necessitates the development of a reliable diagnostic tool that can distinguish between the five RVLS lineages as well as the parental classical LSDV strains, using a single polymerase chain reaction (PCR) and sequencing assay. The current methods are based on the targeted amplification and sequencing of selected gene regions of ORF LW035 that encode the RNA polymerase 30 kDa subunit (RPO30) and the G-protein-coupled chemokine receptor (GPCR) gene encoded by ORF LW011 that have sufficient polymorphism to differentiate between LSDV isolates [29,30]. These gene regions were designed to distinguish Neethling-based vaccines in Cluster 1.1 from field isolates in Cluster 1.2 [29,30]. These markers were previously useful for differentiating capripoxviruses, but their resolution is insufficient to identify and characterize all recombinant strains, necessitating the sequencing of more than one amplicon [21,22,31]. This is particularly important during LSD vaccination campaigns using homologous vaccines because there are currently no assays or commercial kits capable of differentiating between all novel RVLSs and LAVs or classical field isolates [24,32]. Furthermore, a reliable, cost-effective, and rapid approach with higher resolution capability is required to identify the RVL LSDVs circulating in Southeast Asia.
The aim of this study was to identify a region with significant informative polymorphisms capable of distinguishing all the currently known LSDV novel RVLS lineages from commercially available LAV strains in a single assay.

2. Materials and Methods

2.1. Sequences and Primer Design

The whole-genome sequences of all novel recombinant viruses currently available, as well as the identified parental sequences, were used to identify a suitable locus capable of differentiating between the seven clusters [24]. The sequences and metadata for the corresponding isolate used in this analysis are provided in Table 1. The locus capable of differentiating between the isolates was manually searched for using an alignment of the whole-genome sequences. The locus was chosen because it had informative polymorphisms that could be used to uniquely distinguish each of the recombinant strains from the parental or other classical strains, and it could be determined in a single sequencing reaction. The locus, ORF LW134, which encodes a variola virus B22R-like protein [4], was identified as a putative candidate locus in this study. Both the alignment and the primer design were performed using CLC Genomics Workbench v9 (Qiagen, Hilden, Germany). The primer sequences LW134-F (GGT GTG CTG GGA TAT ATT GGC) and LW134-R (CAG TTA AAA CAT CCT CAA ATG CC) were designed to amplify a 705-bp region of the C-terminal region of ORF LW134.

2.2. Samples

The assay was first developed based on an in-silico approach using Genbank sequences (Table 1), and then validated using clinical samples containing DNA from the strains Saratov (Russia 2017), Udmutiya (Russia 2019), Tyumen (Russia 2019), and Dagestan (Russia 2015).
To validate the new single PCR and sequencing assay, skin scabs from eight previously uncharacterized archived samples received from active outbreaks in the Russian Federation between 2018 and 2021 were used. These samples were submitted from Krasnodar in 2016, Kalmykiya in 2016, Voronezh in 2016, Tambov in 2016, Kurgan in 2018 [37], Zabaykalskii Kray in 2021 [25], Altay in 2020, and Buryatiya in 2021, and were selected based on inconclusive typing using previously described assays for differentiating infected from vaccinated animals [25,37].

2.3. DNA Extraction and PCR

The skin scab samples were crushed with a sterile grinder, and total DNA was extracted using the phenol-chloroform (Trizol, Invitrogen, Waltham, MA, USA) method as described by Szpara et al. [38], with some modifications [38,39].
The optimized PCR mixture contained 10 μL of extracted DNA (diluted to an approximate concentration of 10 ng/uL), 15 pM of each primer, 10 μL of PCR buffer (Promega, Madison, WI, USA), MgCl2, dNTPs, and nuclease-free water to a final volume of 50 μL. The PCR was performed on a thermocycler C-1000 (Biorad, Hercules, CA, USA) with the following thermal cycling conditions: 95 °C for 5 min, followed by 40 cycles of 95 °C for 15 s and 60 °C for 40 s.

2.4. Sequence Analysis

Individual sequencing reactions were performed using both primers used in the amplicon generation on an Applied Biosystems genetic analyzer (Applied Biosystems, Waltham, MA, USA). The two sequences were assembled, and a consensus sequence representing each isolate was generated. These consensus sequences were aligned using CLC WorkBench v9 software, and a maximum likelihood phylogeny analysis was performed using MEGA 10 software [40].

3. Results

3.1. Locus Identification

There are currently five novel recombinant clusters described (Clusters 2.1–2.5) [25]. Whole-genome sequences representing each of these clusters, as well as strains identified as parental donors (Neethling vaccine/LW1959 and KSGPO-like), were used to identify a region capable of distinguishing between all seven aforementioned clusters (Table 1). A part of the C-terminal region of ORF LW134 was found to harbor 13 single nucleotide polymorphisms (SNPs) that, when analyzed together, were capable of distinguishing between each of the seven aforementioned clusters (Table 2). Primers were designed to amplify a 705-bp region of ORF LW134, where 13 SNP sites were found to differentiate the Neethling vaccine/LW1959 from KSGPO-240. The RVLS shared eight (Saratov 2017), six (Udmurtiya 2019), three (Konstanay 2018), five (Tyumen 2019), and ten (China 2019) SNPs with Neethling vaccine/LW1959 and the remaining SNPs with KSGPO-2490 (Table 2).

3.2. Assay Validation

Samples submitted to the Russian Federal Centre for Animal Health (FGBI ARRIAH) between 2018 and 2021, previously shown to be recombinants, whereas only field isolates before 2017 [22] were subjected to PCR and sequencing to validate this novel assay (Figure 1). Based on the sequencing results obtained with this assay, a putatively new recombinant lineage was identified (Kurgan 2018) [37]. The putative new recombinant strain status should be confirmed by whole-genome sequencing (Figure 1). Despite the fact that isolate Kurgan 2018 was previously reported to contain a GPCR target similar to KSGPO-240 [37], this assay classified it as a new lineage 2.6 (Figure 1). The remaining samples were successfully clustered within one of the previously described lineages [24] (Figure 1). Despite being verified in-silico, the assay’s usefulness was confirmed by PCR and sequencing of additional unique vaccine-like recombinant isolates from Russia (Figure 1).

4. Discussion

The rapid and extensive spread of LSD has highlighted the need for additional research into the diagnostics and molecular evolution of this high-impact pathogen [15,41]. Although whole-genome sequence analysis remains the gold standard for addressing these challenges, it is time-consuming and expensive. Therefore, faster and less expensive PCR-based approaches are required as alternatives for routine work [24,42].
In this study, we analyzed the available LSDV sequences in Genbank for the presence of loci harboring SNPs sufficient to achieve resolution across the available and circulating strains, in order to differentiate between the recombinant strains. These RVLSs are naturally occurring byproducts of virus evolution that incorporate recombination between vaccine strains [43]. As a result, a suitable locus in ORF LW134 with 13 nucleotide substitutions among the analyzed sequences was discovered, allowing individual clustering in the phylogenetic tree. This clustering is highly similar to what is obtained when whole-genome sequences are analyzed (Table 2). The N-terminal region of ORF134 has previously been used as a sequencing target to differentiate between field isolates from Clusters 1.1 and 1.2, but it is not capable of differentiating between all the novel RVLSs [44]. However, since the multiple RVLSs have emerged as a result of homologous recombination between the vaccine Neethling and KSGP strains, representing both of the aforementioned clusters, this genomic site has gained a new and promising status due to a large number of existing SNPs between the parental strains (Table 2). This ORF encodes the homolog of the variola virus protein B22R, which is present in the majority of the chordopoxvirus genera except for the parapoxvirus genus [45]. This is the largest poxvirus protein, and in LSDV it was subjected to genetic reshuffling and selection of the wild-type genotype in RVLSs [24,46].
Biswas et al. (2019) identified the first LSDV lineage clusters as Cluster 1.1 with vaccine strains and the Neethling type strain [18] and Cluster 1.2 with the KSGPO-2490 vaccine and field isolates from Africa, the Middle East, Europe, Russia, Kazakhstan, and the Indian subcontinent [20]. This study adds Cluster 2.6 with Kurgan 2018 to the previously identified Cluster 2.1 with Saratov 2017 and Saratov 2019, Cluster 2.2 with Udmurtiya 2019, Cluster 2.3 with Kostanay Kazakhstan 2018, Cluster 2.4 with Tyumen 2019, and Cluster 2.5 with Southeastern Asia strains (China 2019, Vietnam 2020, and Khabarovsk 2020) (Figure 1).
PCR assays are well-established, fast, and cost-effective techniques for the laboratory confirmation of a disease or the genotyping of isolates. However, none of the currently available assays could reliably distinguish between vaccine strains or RVLS. Agianniotaki et al. (2017) developed a GPCR-based PCR assay that failed to differentiate between Neethling and KSGP strains and incorrectly identified all virulent RVLSs as vaccine strains [47]. The ORF008-based assay developed by Sprygin et al. (2017) can only identify vaccine strains; however, RVLS retain the vaccine version of ORF008 from 2019 onward, and it may no longer be fit for purpose due to the widespread distribution of such RVLS in Southeast Asia [7]. Vidanovic et al. (2021) developed another ORF008-based assay for field and vaccine strains, but it cannot be used reliably for RVLS outbreaks [48]. In summary, Byadovskaya et al. (2021) provided an overview of the performance of published and commercial Taqman PCR assays [32].
Previously, the molecular targets RPO30, GPCR, and EEV were used for sequencing to distinguish between capripoxviruses or within LSDV between classical strains belonging to Clusters 1.1 and 1.2 [29,30]. Since 2017, novel RVLSs with unique recombination patterns have been identified in active outbreaks, significantly complicating phylogenetic and differentiation molecular analyses [22,31,49]. Unfortunately, the resolutions provided by those loci are insufficient and complicated by the necessity of more than one locus to assign the strain to the recombinant lineage [23].
Given the importance and applications of whole-genome sequencing, as well as its long turnaround time and high cost, a single target approach is required to match the resolution obtained from whole-genome sequencing (Figure 1). Unfortunately, none of the previously described markers were capable of differentiating between all five novel recombinant strains independently, only shedding light on whether a strain of interest belongs to recombinants or not, based on the incongruence of the corresponding trees [22,24]. Therefore, this study was designed to identify and validate a new single locus capable of achieving this, as demonstrated by the ORF LW134 target. The ORF LW134 approach also has the advantage of using a single amplicon and a single sequencing reaction, as opposed to GPCR and RPO30, which require multiple overlapping amplicons [29,30].
In order to validate the newly described assay based on ORF LW134, archived samples submitted from active outbreaks in the Russian Federation between 2018 and 2021 were examined. The samples were found to belong to a new Cluster 2.6 (Kurgan 2018) or group within Clusters 2.1 (Saratov 2019), 2.2 (Samara 2018), or 2.5 with isolates from the Russian Far East, China, and Taiwan. As previously demonstrated, the isolates from 2016 were all assigned to Cluster 1.2 (Figure 1) A new cluster is defined by the creation of a separate branch in a phylogenetic tree. Previously, all field LSDV isolates could be assigned to either Cluster 1.1 or 1.2, but the dominant lineage in Southeast Asia has recently been assigned to Cluster 2.5 [24]. Recent studies have demonstrated that Udmurtiya 2019 and Kostanay 2018 contain the KSGP backbone, in contrast to Saratov 2017, Tomsk 2019, and Khabarovsk 2020, which contain the backbone of the Neethling vaccine strain [21,22,24]. Based on the novel assay, Samara 2018 clusters with Udmurtiya 2019, and whole-genome sequencing of this isolate is required to verify if it has the KSGP backbone. Interestingly, when the whole genomes are analyzed, the former form sister lineages (Clusters 2.3 and 2.2) to the Cluster 1.2 strains, while the latter form sister lineages (Clusters 2.1, 2.4, and 2.5) to the Neethling group (Cluster 1.1). Whole-genome sequencing should provide more clarification on phylogenetic affiliation and recombinant patterns to contribute to a better understanding of fundamental LSDV molecular evolution, but it was beyond the scope of this work to provide insights into these challenges.
Notably, Altay 2020, Buryatiya 2021, and Zabaikalsky 2021 from the Russian Far East [25] clustered with Tomsk 2019, Khabarovsk 2020, and other Southeast Asian isolates in Cluster 2.5 (Figure 1), indicating that this cluster has established itself as the dominant lineage in the region, having outcompeted the other reported lineages [25,35]. Interestingly, the majority of the identified RVLS have unique recombination patterns, implying that no two are similar. However, Saratov 2017 and Saratov 2019 shared significant sequence identity and were detected in the same region two years apart, indicating RVLS’s ability to overwinter under the prevailing conditions of the northern hemisphere [50], which is one of the novel features associated with RVLSs, along with indirect contact transmission of LSDV [51]. These unique phenotypic properties should be investigated in relation to the genomic alterations caused by recombination between two vaccine LSDV strains [5], namely the Neethling-based and KSGPO-like vaccines identified in the KEVIVAPI vaccine [52].
In conclusion, this study describes the identification and validation of a novel target region capable of distinguishing recombinant strains. It was further validated by sequencing previously uncharacterized RVLSs. The ORF134 approach has the potential to be used as a reliable target for molecular evolutionary studies on LSDV isolates, particularly those found in Southeast Asia.

Author Contributions

Conceptualization, A.M., A.v.S., L.P. and A.S.; Data curation, A.K., A.M., A.v.S. and A.S.; Formal analysis, A.K. and O.G.; Funding acquisition, L.P., O.B., I.C. and A.S.; Investigation, A.K., A.M., A.v.S. and O.G.; Project administration, I.C.; Resources, O.B.; Software, A.v.S.; Supervision, A.S.; Validation, A.K.; Writing—original draft, A.M., A.v.S. and A.S.; Writing—review & editing, A.M., A.v.S., O.B., I.C. and A.S. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by the grant no. 075-15-2021-1054 from the Ministry of Education and Science of Russia to implement objectives of the Federal Scientific and Technical Program for the Development of genetic technologies during 2019–2027.

Data Availability Statement

All data reported in this study are available within the manuscript and in Genbank.

Conflicts of Interest

The authors declare they have no conflict of interests.

Ethics Declarations

Ethics approval and consent to participate. The authors confirm that the ethical policies of the journal, as noted in the journal’s author guidelines page, have been adhered to. Samples used in this study were those submitted to FGBI “Federal Centre for Animal Health” (FGBI “ARRIAH”), for LSD diagnosis. Ethical approval was not required.

References

  1. Babiuk, S.; Bowden, T.R.; Boyle, D.B.; Wallace, D.B.; Kitching, R.P. Capripoxviruses: An emerging worldwide threat to sheep, goats and cattle. Transbound. Emerg. Dis. 2008, 55, 263–272. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  2. OIE—Listed Diseases, Infections and Infestations in Force in 2021. OIE—Terrestrial Animal Health Code, Twenty-Eighth Edition. 2019. Available online: https://www.woah.org/fileadmin/Home/eng/Health_standards/tahm/2.04.13_LSD.pdf) (accessed on 14 November 2022).
  3. Hamdi, J.; Munyanduki, H.; Omari Tadlaoui, K.; El Harrak, M.; Fassi Fihri, O. Capripoxvirus Infections in Ruminants: A Review. Microorganisms 2021, 23, 902. [Google Scholar] [CrossRef] [PubMed]
  4. Tulman, E.R.; Afonso, C.L.; Lu, Z.; Zsak, L.; Kutish, G.F.; Rock, D.L. Genome of lumpy skin disease virus. J. Virol. 2001, 75, 7122–7130. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  5. Kononov, A.; Byadovskaya, O.; Wallace, D.; Prutnikov, P.; Pestova, Y.; Kononova, S.; Nesterov, A.; Rusaleev, V.; Lozovoy, D.; Sprygin, A. Non-vector-borne transmission of lumpy skin disease virus. Sci. Rep. 2020, 10, 7436. [Google Scholar] [CrossRef]
  6. Hansen, S.; Pessôa, R.; Nascimento, A.; El-Tholoth, M.; Abd El Wahed, A.; Sanabani, S.S. Dataset of the microbiome composition in skin lesions caused by lumpy skin disease virus via 16s rRNA massive parallel sequencing. Data Brief 2019, 27, 104764. [Google Scholar] [CrossRef] [PubMed]
  7. Sprygin, A.; Pestova, Y.; Prutnikov, P.; Kononov, A. Detection of vaccine-like lumpy skin disease virus in cattle and Musca domestica L. flies in an outbreak of lumpy skin disease in Russia in 2017. Transbound. Emerg. Dis. 2018, 65, 1137–1144. [Google Scholar] [CrossRef]
  8. Wang, Y.; Zhao, L.; Yang, J.; Shi, M.; Nie, F.; Liu, S.; Wang, Z.; Huang, D.; Wu, H.; Li, D.; et al. Analysis of vaccine-like lumpy skin disease virus from flies near the western border of China. Transbound. Emerg. Dis. 2022, 69, 1813–1823. [Google Scholar] [CrossRef]
  9. Ahmed, E.M.; Eltarabilli, M.M.A.; Shahein, M.A.; Fawzy, M. Lumpy skin disease outbreaks investigation in Egyptian cattle and buffaloes: Serological evidence and molecular characterization of genome termini. Comp. Immunol. Microbiol. Infect. Dis. 2021, 76, 101639. [Google Scholar] [CrossRef]
  10. Hasib, F.M.Y.; Islam, M.S.; Das, T.; Rana, E.A.; Uddin, M.H.; Bayzid, M.; Nath, C.; Hossain, M.A.; Masuduzzaman, M.; Das, S.; et al. Lumpy skin disease outbreak in cattle population of Chattogram, Bangladesh. Vet. Med. Sci. 2021, 7, 1616–1624. [Google Scholar] [CrossRef]
  11. Molini, U.; Boshoff, E.; Niel, A.; Phillips, J.; Khaiseb, S.; Settypalli, T.; Dundon, W.; Cattoli, G.; Lamien, C. Detection of Lumpy Skin Disease Virus in an Asymptomatic Eland (Taurotragus oryx) in Namibia. J. Wildl. Dis. 2021, 57, 708–711. [Google Scholar] [CrossRef]
  12. Alkhamis, M.A.; VanderWaal, K. Spatial and temporal epidemiology of lumpy skin disease in the Middle East, 2012–2015. Front. Vet. Sci. 2016, 3, 19. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  13. Agianniotaki, E.; Tasioudi, K.; Chaintoutis, S.; Iliadou, P.; Mangana-Vougiouka, O.; Kirtzalidou, A.; Alexandropoulos, T.; Sachpatzidis, A.; Plevraki, E.; Dovas, C.; et al. Lumpy skin disease outbreaks in Greece during 2015–16, implementation of emergency immunization and genetic differentiation between field isolates and vaccine virus strains. Vet. Microbiol. 2017, 201, 78–84. [Google Scholar] [CrossRef] [PubMed]
  14. Khan, Y.R.; Ali, A.; Hussain, K.; Ijaz, M.; Rabbani, A.H.; Khan, R.L.; Abbas, S.N.; Aziz, M.U.; Ghaffar, A.; Sajid, H.A. A review: Surveillance of lumpy skin disease (LSD) a growing problem in Asia. Microb. Pathog. 2021, 158, 105050. [Google Scholar] [CrossRef] [PubMed]
  15. Kumar, N.; Chander, Y.; Kumar, R.; Khandelwal, N.; Riyesh, T.; Chaudhary, K.; Shanmugasundaram, K.; Kumar, S.; Kumar, A.; Gupta, M.; et al. Isolation and characterization of lumpy skin disease virus from cattle in India. PLoS ONE 2021, 16, e0241022. [Google Scholar] [CrossRef]
  16. Lu, G.; Xie, J.; Luo, J.; Shao, R.; Jia, K.; Li, S. Lumpy skin disease outbreaks in China, since 3 August 2019. Transbound. Emerg. Dis. 2020, 68, 216–219. [Google Scholar] [CrossRef]
  17. Sprygin, A.; Babin, Y.; Pestova, Y.; Kononova, S.; Byadovskaya, O.; Kononov, A. Complete genome sequence of the lumpy skin disease virus recovered from the first outbreak in the Northern Caucasus Region of Russia in 2015. Microbiol. Resour. Announc. 2019, 8, e01733-18. [Google Scholar] [CrossRef] [Green Version]
  18. Biswas, S.; Noyce, R.; Babiuk, L.; Lung, O.; Bulach, D.; Bowden, T.; Boyle, D.; Babiuk, S.; Evans, D. Extended sequencing of vaccine and wild-type capripoxvirus isolates provides insights into genes modulating virulence and host range. Transbound. Emerg. Dis. 2019, 67, 80–97. [Google Scholar] [CrossRef]
  19. Van Schalkwyk, A.; Byadovskaya, O.; Shumilova, I.; Wallace, D.; Sprygin, A. Estimating evolutionary changes between highly passaged and original parental lumpy skin disease virus strains. Trans. Emer. Dis. 2021, 69, e486–e496. [Google Scholar] [CrossRef]
  20. Van Schalkwyk, A.; Kara, P.; Heath, L. Phylogenomic characterization of historic lumpy skin disease virus isolates from South Africa. Arch. Virol. 2022, 167, 2063–2070. [Google Scholar] [CrossRef]
  21. Sprygin, A.; Babin, Y.; Pestova, Y.; Kononova, S.; Wallace, D.B.; Van Schalkwyk, A.; Kononov, A. Analysis and insights into recombination signals in lumpy skin disease virus recovered in the field. PLoS ONE 2018, 13, e0207480. [Google Scholar] [CrossRef]
  22. Sprygin, A.; Van Schalkwyk, A.; Shumilova, I.; Nesterov, A.; Kononova, S.; Prutnikov, P.; Byadovskaya, O.; Kononov, A. Full-length genome characterization of a novel recombinant vaccine-like lumpy skin disease virus strain detected during the climatic winter in Russia, 2019. Arch. Virol. 2020, 165, 2675–2677. [Google Scholar] [CrossRef] [PubMed]
  23. Sprygin, A.; Pestova, Y.; Bjadovskaya, O.; Prutnikov, P.; Zinyakov, N.; Kononova, S.; Ruchnova, O.; Lozovoy, D.; Chvala, I.; Kononov, A. Evidence of recombination of vaccine strains of lumpy skin disease virus with field strains, causing disease. PLoS ONE. 2020, 13, e0232584. [Google Scholar] [CrossRef] [PubMed]
  24. Krotova, A.; Byadovskaya, O.; Shumilova, I.; van Schalkwyk, A.; Sprygin, A. An in-depth bioinformatic analysis of the novel recombinant lumpy skin disease virus strains: From unique patterns to established lineage. BMC Genom. 2022, 23, 396. [Google Scholar] [CrossRef] [PubMed]
  25. Krotova, A.; Mazloum, A.; Byadovskaya, O.; Sprygin, A. Phylogenetic analysis of lumpy skin disease virus isolates in Russia in 2019–2021. Arch. Virol. 2022, 167, 1693–1699. [Google Scholar] [CrossRef]
  26. Tran, H.; Truong, A.; Dang, A.; Ly, D.; Nguyen, C.; Chu, N.; Hoang, T.; Nguyen, H.; Nguyen, V.; Dang, H. Lumpy skin disease outbreaks in Vietnam, 2020. Trans. Emer. Dis. 2021, 68, 977–980. [Google Scholar] [CrossRef] [PubMed]
  27. Singhla, T.; Boonsri, K.; Kreausukon, K.; Modethed, W.; Pringproa, K.; Sthitmatee, N.; Vinitchaikul, P. Molecular Characterization and Phylogenetic Analysis of Lumpy Skin Disease Virus Collected from Outbreaks in Northern Thailand in 2021. Vet. Sci. 2022, 9, 194. [Google Scholar] [CrossRef]
  28. Wang, J.; Xu, Z.; Wang, Z.; Li, Q.; Liang, X.; Ye, S.; Li, S. Isolation, identification and phylogenetic analysis of lumpy skin disease virus strain of outbreak in Guangdong, China. Transbound. Emerg. Dis. 2022, 69, e2291–e2301. [Google Scholar] [CrossRef]
  29. Lamien, C.E.; Le Goff, C.; Silber, R.; Wallace, D.B.; Gulyaz, V.; Tuppurainen, E.; Madani, H.; Caufour, P.; Adam, T.; El Harrak, M.; et al. Use of the Capripoxvirus homologue of Vaccinia virus 30 kDa RNA polymerase subunit (RPO30) gene as a novel diagnostic and genotyping target: Development of a classical PCR method to differentiate Goat poxvirus from Sheep poxvirus. Vet. Microbiol. 2011, 149, 30–39. [Google Scholar] [CrossRef]
  30. Le Goff, C.; Lamien, C.E.; Fakhfakh, E.; Chadeyras, A.; Aba-Adulugba, E.; Libeau, G.; Tuppurainen, E.; Wallace, D.B.; Adam, T.; Silber, R.; et al. Capripoxvirus G-protein-coupled chemokine receptor: A host-range gene suitable for virus animal origin discrimination. J. Gen. Virol. 2009, 90, 1967–1977. [Google Scholar] [CrossRef]
  31. Koirala, P.; Meki, I.K.; Maharjan, M.; Settypalli, B.K.; Manandhar, S.; Yadav, S.K.; Cattoli, G.; Lamien, C.E. Molecular Characterization of the 2020 Outbreak of Lumpy Skin Disease in Nepal. Microorganisms 2022, 10, 539. [Google Scholar] [CrossRef]
  32. Byadovskaya, O.; Pestova, Y.; Kononov, A.; Shumilova, I.; Kononova, S.; Nesterov, A.; Babiuk, S.; Sprygin, A. Performance of the currently available DIVA real-time PCR assays in classical and recombinant lumpy skin disease viruses. Transbound. Emerg. Dis. 2021, 68, 3020–3024. [Google Scholar] [CrossRef] [PubMed]
  33. Kara, P.D.; Afonso, C.L.; Wallace, D.B.; Kutish, G.F.; Abolnik, C.; Lu, Z.; Vreede, F.T.; Taljaard, L.C.F.; Zack, A.; Viljoen, G.J.; et al. Comparative sequence analysis of the South African vaccine strain and two virulent field isolates of lumpy skin disease virus. Arc. Virol. 2003, 148, 1335–1356. [Google Scholar] [CrossRef] [PubMed]
  34. Vandenbussche, F.; Mathijs, E.; Haegeman, A.; Al-Majali, A.; Van Borm, S.; De Clercq, K. Complete genome sequence of Capripoxvirus strain KSGP 0240 from a commercial live attenuated vaccine. Genome Announc. 2016, 4, e01114-16. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  35. Krotova, A.; Byadovskaya, O.; Shumilova, I.; Zinyakov, N.; van Schalkwyk, A.; Sprygin, A. Molecular characterization of a novel recombinant lumpy skin disease virus isolated during an outbreak in Tyumen, Russia, in 2019. Transbound. Emerg. Dis. 2022, 69, e2312–e2317. [Google Scholar] [CrossRef] [PubMed]
  36. Ma, J.; Yuan, Y.; Shao, J.; Sun, M.; He, W.; Chen, J.; Liu, Q. Genomic characterization of lumpy skin disease virus in southern China. Transbound. Emerg. Dis. 2021, 69, 2788–2799. [Google Scholar] [CrossRef]
  37. Kononov, A.; Prutnikov, P.; Byadovskaya, O.; Kononova, S.; Rusaleev, V.; Pestova, Y.; Sprygin, A. Emergence of a new lumpy skin disease virus variant in Kurgan Oblast, Russia, in 2018. Arch. Virol. 2020, 165, 1343–1356. [Google Scholar] [CrossRef]
  38. Szpara, M.L.; Tafuri, Y.R.; Enquist, L.W. Preparation of viral DNA from nucleocapsids. JoVE 2011, 54, e3151. [Google Scholar] [CrossRef]
  39. Mazloum, A.; van Schalkwyk, A.; Shotin, A.; Igolkin, A.; Shevchenko, I.; Gruzdev, K.N.; Vlasova, N. Comparative analysis of full genome sequences of African swine fever virus isolates taken from wild boars in Russia in 2019. Pathogens 2021, 10, 521. [Google Scholar] [CrossRef]
  40. Kumar, S.; Stecher, G.; Li, M.; Knyaz, C.; Tamura, K. MEGA X: Molecular evolutionary genetics analysis across computing platforms. Mol. Biol. Evol. 2018, 35, 1547. [Google Scholar] [CrossRef]
  41. Byadovskaya, O.; Prutnikov, P.; Shalina, K.; Babiuk, S.; Perevozchikova, N.; Korennoy, F.; Sprygin, A. The changing epidemiology of lumpy skin disease in Russia since the first introduction from 2015 to 2020. Transbound. Emerg. Dis. 2022, 69, e2551–e2562. [Google Scholar] [CrossRef] [PubMed]
  42. Tsai, K.J.; Tu, Y.C.; Wu, C.H.; Huang, C.W.; Ting, L.J.; Huang, Y.L.; Lee, F. First detection and phylogenetic analysis of lumpy skin disease virus from Kinmen Island, Taiwan in 2020. J. Vet. Med. Sci. 2022, 84, 1093–1100. [Google Scholar] [CrossRef] [PubMed]
  43. Sprygin, A.; Mazloum, A.; van Schalkwyk, A.; Babiuk, S. Capripoxviruses, leporipoxviruses, and orthopoxviruses: Occurrences of recombination. Front. Microbiol. 2022, 13, 978829. [Google Scholar] [CrossRef] [PubMed]
  44. Van Schalkwyk, A.; Kara, P.; Ebersohn, K.; Mather, A.; Annandale, C.H.; Venter, E.H.; Wallace, D.B. Potential link of single nucleotide polymorphisms to virulence of vaccine-associated field strains of lumpy skin disease virus in South Africa. Transbound. Emerg. Dis. 2020, 67, 2946–2960. [Google Scholar] [CrossRef] [PubMed]
  45. Tulman, E.R.; Delhon, G.; Afonso, C.L.; Lu, Z.; Zsak, L.; Sandybaev, N.T.; Kerembekova, U.Z.; Zaitsev, V.L.; Kutish, G.F.; Rock, D.L. Genome of Horsepox virus. J. Virol. 2006, 80, 9244–9258. [Google Scholar] [CrossRef] [Green Version]
  46. Sprygin, A.; Artyuchova, E.; Babin, Y.; Prutnikov, P.; Kostrova, E.; Byadovskaya, O.; Kononov, A. Epidemiological characterization of lumpy skin disease outbreaks in Russia in 2016. Transbound. Emerg. Dis. 2018, 65, 1514–1521. [Google Scholar] [CrossRef]
  47. Agianniotaki, E.I.; Chaintoutis, S.; Haegeman, A.; Tasioudi, K.E.; De Leeuw, I.; Katsoulos, P.-D.; Sachpatzidis, A.; De Clercq, K.; Alexandropoulos, T.; Polizopoulou, Z.S.; et al. Development and validation of a TaqMan probe-based real-time PCR method for the differentiation of wild type lumpy skin disease virus from vaccine virus strains. J. Virol. Methods 2017, 249, 48–57. [Google Scholar] [CrossRef]
  48. Vidanović, D.; Tešović, B.; Šekler, M.; Debeljak, Z.; Vasković, N.; Matović, K.; Koltsov, A.; Krstevski, K.; Petrović, T.; De Leeuw, I.; et al. Validation of TaqMan-Based Assays for Specific Detection and Differentiation of Wild-Type and Neethling Vaccine Strains of LSDV. Microorganisms 2021, 9, 1234. [Google Scholar] [CrossRef]
  49. Badhy, S.C.; Chowdhury, M.G.A.; Settypalli, T.B.K.; Cattoli, G.; Lamien, C.E.; Fakir, M.A.U.; Akter, S.; Osmani, M.G.; Talukdar, F.; Begum, N.; et al. Molecular characterization of lumpy skin disease virus (LSDV) emerged in Bangladesh reveals unique genetic features compared to contemporary field strains. BMC Vet. Res. 2021, 17, 61. [Google Scholar] [CrossRef]
  50. Shumilova, I.; Krotova, A.; Nesterov, A.; Byadovskaya, O.; van Schalkwyk, A.; Sprygin, A. Overwintering of recombinant lumpy skin disease virus in northern latitudes, Russia. Transbound. Emerg. Dis. 2022, 69, e3239–e3243. [Google Scholar] [CrossRef]
  51. Nesterov, A.; Mazloum, A.; Byadovskaya, O.; Shumilova, I.; Van Schalkwyk, A.; Krotova, A.; Sprygin, A. Experimentally controlled study indicates that the naturally occurring recombinant vaccine-like lumpy skin disease strain Udmurtiya/2019, detected during freezing winter in northern latitudes, is transmitted via indirect contact. Front. Vet. Sci. 2022, 9, 1651. [Google Scholar] [CrossRef]
  52. Vandenbussche, F.; Mathijs, E.; Philips, W.; Saduakassova, M.; De Leeuw, I.; Sultanov, A.; De Clercq, K. Recombinant LSDV Strains in Asia: Vaccine Spillover or Natural Emergence? Viruses 2022, 14, 1429. [Google Scholar] [CrossRef] [PubMed]
Figure 1. Maximum likelihood phylogenetic tree of the 705-bp region within ORF134. Sequences used to design the assay, as well as sequences generated from new samples submitted in 2016 and between 2018 and 2021, were included in the tree. The original two classical clusters (1.1 and 1.2), the previously known five recombinant clusters (Clusters 2.1 to 2.5), and a potential novel lineage (2.6) are indicated in the phylogenetic tree. The samples used for method validation by PCR and sequencing, but not whole-genome sequencing, are defined by black circles.
Figure 1. Maximum likelihood phylogenetic tree of the 705-bp region within ORF134. Sequences used to design the assay, as well as sequences generated from new samples submitted in 2016 and between 2018 and 2021, were included in the tree. The original two classical clusters (1.1 and 1.2), the previously known five recombinant clusters (Clusters 2.1 to 2.5), and a potential novel lineage (2.6) are indicated in the phylogenetic tree. The samples used for method validation by PCR and sequencing, but not whole-genome sequencing, are defined by black circles.
Applmicrobiol 03 00003 g001
Table 1. Whole-genome sequences retrieved from GenBank and used to design a single polymerase chain reaction (PCR) and sequencing assay.
Table 1. Whole-genome sequences retrieved from GenBank and used to design a single polymerase chain reaction (PCR) and sequencing assay.
IsolateClusterGenBank Accession NumberReference
Neethling vaccine LW19591.1AF409138[33]
KSGPO-240 vaccine1.2AF325528[34]
Saratov Russia 20172.1MH646674[17]
Udmutiya Russia 20192.2MT134042[22]
Konstanay Kazakhstan 20182.3MT992618None
Tyumen Russia 20192.4OL542833[35]
GD01 China 20202.5MW355944[36]
Dagestan Russia 20151.2MH893760[17]
Table 2. Position and single nucleotide polymorphisms (SNPs) sites within the 705bp-region of the ORF LW134 gene. The SNPs identical to the Neethling vaccine/LW1959 are displayed in green, whereas those identical to KSGPO-240 are displayed in blue.
Table 2. Position and single nucleotide polymorphisms (SNPs) sites within the 705bp-region of the ORF LW134 gene. The SNPs identical to the Neethling vaccine/LW1959 are displayed in green, whereas those identical to KSGPO-240 are displayed in blue.
Position within the 705 bp AmpliconNeethling Vaccine LW1959KSGPO-240 VaccineDagestan Russia 2015Saratov Russia 2017Udmurtiya Russia 2019Kostanay Kazakhstan 2018Tyumen Russia 2019GD01 China 2020
Cluster1.11.21.22.12.22.32.42.5
34TCCCTCCT
39TCCCTCCT
48AGGGAGGA
186GAAGGAAA
242CTTCTTTC
249GCCGCCCC
256AGGAGGGA
370TCCTCCTT
389CTTCTTCC
407GAAGAAGG
452TCCCCTCC
551TCCTTTTT
621GTTTGGGG
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MDPI and ACS Style

Krotova, A.; Mazloum, A.; van Schalkwyk, A.; Prokhvatilova, L.; Gubenko, O.; Byadovskaya, O.; Chvala, I.; Sprygin, A. The Characterization and Differentiation of Recombinant Lumpy Skin Disease Isolates Using a Region within ORF134. Appl. Microbiol. 2023, 3, 35-44. https://doi.org/10.3390/applmicrobiol3010003

AMA Style

Krotova A, Mazloum A, van Schalkwyk A, Prokhvatilova L, Gubenko O, Byadovskaya O, Chvala I, Sprygin A. The Characterization and Differentiation of Recombinant Lumpy Skin Disease Isolates Using a Region within ORF134. Applied Microbiology. 2023; 3(1):35-44. https://doi.org/10.3390/applmicrobiol3010003

Chicago/Turabian Style

Krotova, Alena, Ali Mazloum, Antoinette van Schalkwyk, Larisa Prokhvatilova, Olesya Gubenko, Olga Byadovskaya, Ilya Chvala, and Alexander Sprygin. 2023. "The Characterization and Differentiation of Recombinant Lumpy Skin Disease Isolates Using a Region within ORF134" Applied Microbiology 3, no. 1: 35-44. https://doi.org/10.3390/applmicrobiol3010003

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