| Literature DB >> 29096657 |
Meripet Polat1,2, Shin-Nosuke Takeshima1,2,3, Yoko Aida4,5,6.
Abstract
Bovine leukemia virus (BLV), an oncogenic member of the Deltaretrovirus genus, is closely related to human T-cell leukemia virus (HTLV-I and II). BLV infects cattle worldwide and causes important economic losses. In this review, we provide a summary of available information about commonly used diagnostic approaches for the detection of BLV infection, including both serological and viral genome-based methods. We also outline genotyping methods used for the phylogenetic analysis of BLV, including PCR restriction length polymorphism and modern DNA sequencing-based methods. In addition, detailed epidemiological information on the prevalence of BLV in cattle worldwide is presented. Finally, we summarize the various BLV genotypes identified by the phylogenetic analyses of the whole genome and env gp51 sequences of BLV strains in different countries and discuss the distribution of BLV genotypes worldwide.Entities:
Keywords: BLV diagnostic approches; BLV epidemiology; BLV genotyping methods; Bovine leukemia virus (BLV)
Mesh:
Substances:
Year: 2017 PMID: 29096657 PMCID: PMC5669023 DOI: 10.1186/s12985-017-0876-4
Source DB: PubMed Journal: Virol J ISSN: 1743-422X Impact factor: 4.099
Fig. 1Schematic representations of the BLV genome structure (a) and viral particle (b). The structural and enzymatic genes, gag, pro, pol, and env; regulatory genes, tax and rex; accessory genes R3 and G4; and microRNA (miRNA) are indicated in (a). Proteins encoded by structural and enzymatic genes, including the Env glycoproteins (gp51 and gp30) encoded by the env gene, the Gag proteins (p12, p24, and p15) encoded by the gag gene, reverse transcriptase and integrase (RT-IN) encoded by the pol gene, and protease (Pro) encoded by the pro gene are indicated in (b)
Summary of common techniques used for diagnosis of BLV prevalence
| Diagnostic assay | Sample | Target | Advantages | Disadvantages | References | |
|---|---|---|---|---|---|---|
| Type | Assay | |||||
| Serological test | AGID | Serum | Antibodies (p24, gp51) | Specific, simple, and easy to perform Large scale screening Less expensive | Less sensitive and inconclusive Cannot evaluate disease states of infected cattle | Aida et al., 1989 [ |
| Wang et al., 1991 [ | ||||||
| Monti et al., 2005 [ | ||||||
| Kurdi et al., 1999 [ | ||||||
| Jimba et al., 2012 [ | ||||||
| Naif et al., 1990 [ | ||||||
| ELISA | Serum Milk Bulk milk | Antibodies (p24, gp51) | Specific and sensitive Large scale screening Time saving | False negatives (cattle in early infection phase) False positive (maternally derived antibodies) Cannot evaluate disease states of infected cattle A number of controls and a plate reader required Results require interpretation | Naif et al., 1990 [ | |
| Burridge et al., 1982 [ | ||||||
| Schoepf et al., 1997 [ | ||||||
| Kurdi et al., 1999 [ | ||||||
| Monti et al., 2005 [ | ||||||
| Jimba et al., 2012 [ | ||||||
| Zaghawa et al., 2002 [ | ||||||
| PHA | Virus particle | BLV glycoprotein | Sensitive Specific detection of BLV Large scale titration Less expensive | Affected by pH and temperature Hemagglutination activity reduced by trypsin, potassium periodate, and neuraminidase | Fukai et al., 1999 [ | |
| RIA | Serum | Antibodies (p24) | Sensitive Able to detect BLV during the early period of infection | Cannot be used for mass screening | Levy et al., 1977 [ | |
| Nguyen et al., 1993 [ | ||||||
| Proviral DNA detection | Single PCR; Semi-nested PCR; Nested PCR | Blood PBMC Tumor sample Buffy coat Milk somatic cells | Provirus | Direct, fast, sensitive A variety of samples can be used BLV detection during the early phase of infection or in the presence of colostrum antibodies | Unable to detect BLV when the proviral load is too low | Monti et al., 2005 [ |
| Kurdi et al., 1999 [ | ||||||
| Zaghawa et al., 2002 [ | ||||||
| Tajima et al., 1998 [ | ||||||
| Tajima et al., 2003 [ | ||||||
| Real-time PCR | Blood PBMC Tumor sample Buffy coat Milk | Provirus | Direct, fast, sensitive Low risk of contamination A variety of samples can be used Distinguishes EBL from SBL BLV can be detected during the early phase of infection or in the presence of colostrum antibodies Quantitative measurement of proviral load | Requires internal control Requires positive controls of different concentrations Requires specific primers and probes Require equipment (real-time PCR machine) Expensive | Somura et al., 2014 [ | |
| Lew et al., 2004 [ | ||||||
| Jimba et al., 2010 [ | ||||||
| Jimba et al., 2012 [ | ||||||
| Tawfeeq et al., 2013 [ | ||||||
| Brym et al., 2013 [ | ||||||
| Takeshima et al., 2015 [ | ||||||
| Direct blood-based PCR | Blood | Provirus | Cost-effective No need for DNA purification Low risk of contamination | Unable to detect BLV when the proviral load is too low | Nishimori et al., 2016 [ | |
| Takeshima et al., 2016 [ | ||||||
AGID agar gel immunodiffusion, BLV bovine leukemia virus, EBL enzootic bovine leukosis, ELISA enzyme-linked immunosorbent assay, PHA passive hemagglutination assay, RIA radio immunoassay
Summary of BLV genotyping methods
| Genotyping method | Amplified BLV region | Amplicon size (bp) | Enzymes | Phylogenetic approaches | Classification result | Reference |
|---|---|---|---|---|---|---|
| PCR-RFLP | Partial | 444 |
| 7 groups: A, B, C, D, E, F, G | Fechner et al., 1997 [ | |
| Licursi et al., 2002 [ | ||||||
| Asfaw et al., 2005 [ | ||||||
| RFLP + sequencing | Partial | 400–444 |
| NJ; MP; ML | RFLP-based type: Australian type, Argentine type, Belgium type, Japanese type; Sequence-based type: Argentine cluster, European cluster, Japan and German isolate cluster; groups I–IV; or genotypes 1–8 | Monti et al., 2005 [ |
| Felmer et al., 2005 [ | ||||||
| Camargos et al., 2007 [ | ||||||
| PCR-sequencing | Partial | 346–444 | NJ; ML; BI | Japanese group, Argentine group, European group; or genotypes 1–8 | Camargos et al., 2002 [ | |
| Licursi et al., 2003 [ | ||||||
| Matsumura et al., 2011 [ | ||||||
| Rola-Luszczak et al., 2013 [ | ||||||
| Polat et al., 2015 [ | ||||||
| Ochirkhuu et al., 2016 [ | ||||||
| Polat et al., 2016 [ | ||||||
| Sequencing of partial or full | 444–903 | NJ; ML; BI | Up to 10 BLV genotypes | Moratorio et al., 2010 [ | ||
| Balic et al., 2012 [ | ||||||
| Lee et al., 2015 [ | ||||||
| Lee et al., 2016 [ | ||||||
| Sequencing of | up to 1548 | NJ; ML; BI | Consensus cluster, US Californian cluster, European cluster, Costa Rican cluster; or genotypes 1–10 | Zhao et al., 2007 [ | ||
| Rodriguez et al., 2009 [ | ||||||
| Yang et al., 2016 [ | ||||||
| Full BLV genome sequencing | BLV complete genome | 8714 | ML | genotypes −1, −2, −4, −6, −9, and −10 | Polat et al., 2016 [ |
BI Bayesian inference, BLV bovine leukemia virus, NJ neighbor-joining, ML maximum-likelihood, MP maximum-parsimony, RFLP restriction fragment length polymorphism
Fig. 2Maximum likelihood phylogenetic tree constructed based on partial BLV env sequences identified in geographical locations around the world. A maximum likelihood (ML) phylogenetic tree was constructed based on sequences from known BLV strains, representing ten different BLV genotypes derived from viruses isolated worldwide. Nucleotide sequences were obtained from the GenBank nucleotide sequence database. Sequences are labeled with their accession numbers and countries of origin. Genotypes are indicated by numbers to the right of the figure. One thousand replications were performed to calculate bootstrap values (indicated on the tree). The bar at the bottom of the figure indicates evolutionary distance
Fig. 3Maximum likelihood (ML) phylogenetic tree constructed from complete BLV genomic sequences. The ML phylogenetic tree was constructed using complete BLV genomic sequences from the GenBank nucleotide sequence database. One thousand replications were performed to calculate bootstrap values (indicated on the tree). The strains identified in this study are indicated by the sample identification number and country name. Genotypes are indicated by numbers to the right of the figure. The bar at the bottom of the figure indicates evolutionary distance
Detailed information on BLV infection levels worldwide
| Geographical division | Country | Within country | BLV prevalencea | References |
|---|---|---|---|---|
| Europe | Andorra | Nationwide | BLV-free, 1994 | OIE, 2009 [ |
| Cyprus | Nationwide | BLV-free, 1995 | OIE, 2009 [ | |
| Czech Republic | Nationwide | BLV-free, 2010 | OIE, 2009 [ | |
| Denmark | Nationwide | BLV-free, 1990 | OIE, 2009 [ | |
| Estonia | Nationwide | BLV-free, 2013 | OIE, 2009 [ | |
| Finland | Nationwide | BLV-free, 2008 | OIE, 2009 [ | |
| Ireland | Nationwide | BLV-free, 1999 | OIE, 2009 [ | |
| Norway | Nationwide | BLV-free, 2002 | OIE, 2009 [ | |
| Spain | Nationwide | BLV-free, 1994 | OIE, 2009 [ | |
| Switzerland | Nationwide | BLV-free, 2005 | OIE, 2009 [ | |
| Sweden | Nationwide | BLV-free, 2007 | OIE, 2009 [ | |
| Slovenia | Nationwide | BLV-free, 2006 | OIE, 2009 [ | |
| UK | Nationwide | BLV-free, 1996 | OIE, 2009 [ | |
| The Netherlands | Nationwide | BLV-free, 2009 | OIE, 2012 [ | |
| Poland | BLV-free, 2017 | EFSA Panel on Animal Health and Welfare, 2017 [ | ||
| Ukraine | Present | OIE, 2012 [ | ||
| Croatia | Present | OIE, 2012 [ | ||
| Italy | Present | OIE, 2009 [ | ||
| Portugal | Present | OIE, 2009 [ | ||
| Belarus | Present | OIE, 2012 [ | ||
| Latvia | Present | OIE, 2009 [ | ||
| Romania | Restricted to certain area | OIE, 2009 [ | ||
| Bulgaria | Present | OIE, 2009 [ | ||
| Greece | Present | OIE, 2009 [ | ||
| Oceania | Australia | BLV-free in dairy cattle, 2013 | EPAHW, 2015 [ | |
| New Zealand | BLV-free, 2008 | Chethanond, 1999 [ | ||
| North America | USA | 83.9% dairy cattle; 39% beef cattle, 2007 | APHIS, 2008 [ | |
| Canada | Nationwide | 89% at herd level | APHIS, 2008 [ | |
| Nationwide | 78% at herd level, 1998–2003 | Nekouei, 2015 [ | ||
| Saskatchewan | 37.2% at individual level, 2001 | VanLeeuwen et al., 2001 [ | ||
| Maritime | 20.8% at individual and 70.0% at herd level, 1998–1999 | VanLeeuwen et al., 2005 [ | ||
| Maritime | 30.4% at individual and 90.8% at herd level, 2013 | Nekouei, 2015 [ | ||
| Mexico | Nationwide | 36.1% of dairy and 4.0% of beef cattle, 1983 | Suzan et al., 1983 [ | |
| South America | Brazil | 17.1% to 60.8%, 1980–1989 and 1992–1995 | Sammara et al., 1997 [ | |
| Argentina | Buenos Aires | 77.4% at individual and 90.9% at herd level, 2007 | Polat et al., 2016 [ | |
| Multiple regions | 32.85% at individual and 84% at herd level, 1998–1999 | Trono et al., 2001 [ | ||
| Chile | Southern region | 27.9% at individual level, 2009 | Polat et al., 2016 [ | |
| Bolivia | Multiple regions | 30.7% at individual level, 2008 | Polat et al., 2016 [ | |
| Peru | Multiple regions | 42.3% at individual level, 2008 | Polat et al., 2016 [ | |
| Multiple regions | 31.0% at individual level, 1983 | Ch, 1983 [ | ||
| Venezuela | Nationwide | 33.3% at individual level, 1978 | Marin et al., 1978 [ | |
| Uruguay | Present | Moratorio et al., 2010 [ | ||
| Paraguay | Asuncion | 54.7% at individual level, 2008 | Polat et al., 2016 [ | |
| Colombia | Narino | 19.8% at individual level, 2013 | Benavides et al., 2013 [ | |
| Africa | South Africa | BLV-free, 2012 | OIE, 2012 [ | |
| Tunisia | BLV-free, 2005 | OIE, 2009 [ | ||
| Egypt | BLV-free, 1997 | OIE, 2009 [ | ||
| Asia | Kazakhstan | BLV-free, 2007 | OIE, 2009 [ | |
| Kyrgyzstan | BLV-free, 2008 | OIE, 2009 [ | ||
| China | 49.1% of dairy and 1.6% of beef cattle, 2013–2014 | Yang et al., 2016 [ | ||
| Japan | Nationwide | 40.9% of dairy and 28.7% of beef cattle, 2009–2011 | Murakami et al., 2013 [ | |
| Nationwide | 79.1% of dairy herd, 2007 | Kobayashi et al., 2010 [ | ||
| Nationwide | 28.6% overall; 34.7% of dairy, 16.3% of beef, and 7.9% of fattening beef cattle, 2007 | Murakami et al., 2011 [ | ||
| Nationwide | 73.3% at individual cattle, 2012–2014 | Ohno et al., 2015 [ | ||
| Mongolia | 3.9% of dairy cattle, 2014 | Ochirkhuu et al., 2016 [ | ||
| Cambodia | 5.3% of draught cattle, 2000 | Meas et al., 2000 [ | ||
| Taiwan | 5.8% of dairy cattle, 1986 | Wang et al., 1991 [ | ||
| Iran | Nationwide | Between 22.1% to 25.4%, 2012–2014 | Nekoei et al., 2015 [ | |
| Khorasan Razavi | 29.8% of dairy cattle, 2009 | Mousavi et al., 2014 [ | ||
| Khorasan Shomali | 1.5% of dairy cattle, 2009 | Mousavi et al., 2014 [ | ||
| Thailand | 58.7% of cattle, 2013–2014 | Lee et al., 2016 [ | ||
| Philippines | 4.8% to 9.7% of cattle, 2010–2012 | Polat et al., 2015 [ | ||
| Myanmar | 9.1% at individual level 2016 | Polat et al., 2016 [ | ||
| Korea | 54.2% of dairy cattle and 86.8% of dairy herds; 0.14% of beef cattle, 2014 | Lee et al., 2015 [ | ||
| Middle East | Israeli | 5% at individual level | Trainin & Brenner, 2005 [ | |
| Saudi Arabia | 20.2% of dairy cattle, 1990 | Hafez et al., 1990 [ | ||
| Turkey | 48.3% of dairy herd | Burgu et al., 2005 [ |
BLV prevalence in this table shows BLV infection in certain specific period. Therefore, there might be a change in BLV prevalence in different times
APHIS Animal and Plant Health Inspection Service, BLV bovine leukemia virus, EFSA European Food Safety Authority, EPAHW European Panal on Animal Health and Welfare, OIE The World Organisation for Animal Health
Note: aBLV prevalence in each sample collection year; however, no information about sample collection year was provided in some cases
Worldwide geographical distribution of the ten known BLV genotypes based on env-gp51 sequences
| Geographical division | Country | Genotype | Reference | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | ||||
| Europe | Belarus | 4 | Rola-Luszczak et al., 2013 [ | |||||||||
| Russia | 4 | 7 | 8 | Rola-Luszczak et al., 2013 [ | ||||||||
| Ukraine | 4 | 7 | 8 | Rola-Luszczak et al., 2013 [ | ||||||||
| Croatia | 8 | Balic et al., 2012 [ | ||||||||||
| Poland | 4 | 7 | Rola-Luszczak et al., 2013 [ | |||||||||
| Belgium | 4 | Mamoun et al., 1990 [ | ||||||||||
| France | 3 | 4 | Mamoun et al., 1990 [ | |||||||||
| Germany | 1 | 4 | Fechner et al., 1997 [ | |||||||||
| Italy | 7 | Molteni et al., 1996 [ | ||||||||||
| Australia | Australia | 1 | Coulston et al., 1990 [ | |||||||||
| America | USA | 1 | 3 | 4 | Derse et al., 1985 [ | |||||||
| Caribbean | 1 | Yang et al., 2016 [ | ||||||||||
| Costa Rica | 1 | 5 | Zhao & Buehring, 2007 [ | |||||||||
| Argentina | 1 | 2 | 4 | 6 | Dube et al., 2000 [ | |||||||
| Brazil | 1 | 2 | 5 | 6 | 7 | Camargos et al., 2002 [ | ||||||
| Chile | 4 | 7 | Felmer et al., 2005 [ | |||||||||
| Bolivia | 1 | 2 | 6 | 9 | Polat et al., 2016 [ | |||||||
| Peru | 1 | 2 | 6 | Polat et al., 2016 [ | ||||||||
| Paraguay | 1 | 2 | 6 | Polat et al., 2016 [ | ||||||||
| Uruguay | 1 | Moratorio et al., 2010 [ | ||||||||||
| Asia | Korea | 1 | 3 | Lim et al., 2009 [ | ||||||||
| Japan | 1 | 2 | 3 | Licursi et al., 2003 [ | ||||||||
| Philippines | 1 | 6 | Polat et al., 2015 [ | |||||||||
| Thailand | 1 | 6 | 10 | Lee et al., 2016 [ | ||||||||
| Myanmar | 10 | Polat et al., 2016 [ | ||||||||||
| Mongolia | 1 | 4 | 7 | Ochirkhuu et al., 2016 [ | ||||||||
| Jordan | 1 | 6 | Ababneh et al., 2016 [ | |||||||||