Molecular Detection of Eimeria bovis in Indonesian Beef Cattle Using Nested PCR Technique Article Swipe
YOU?
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· 2024
· Open Access
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· DOI: https://doi.org/10.4308/hjb.31.5.980-987
Eimeria bovis is a pathogenic protozoan that causes cattle digestive tract infections, which can cause economic losses to farmers. It is necessary to develop specific and accurate detection methods to conserve livestock and prevent coccidiosis in Indonesia. This study aims to detect E. bovis by nested PCR and determine the relationship with reference sequences. A total of 167 samples of beef cattle feces were taken randomly from community farms spread across 18 provinces in Indonesia. The feces were examined natively, and then the oocysts were purified by the sugar flotation method, extracted by KIT extraction, and amplified by the nPCR technique. Positive samples were followed by sequencing and phylogenetic analysis using MEGA 11 software. This study used two pairs of primers (outer and inner) taken from ITS-1 molecular markers. As many as 96 out of 167 samples (57.5%) were positive for Eimeria spp., and 48 of the 96 samples were positive for Eimeria spp. (50%) were detected to be positive for E. bovis based on the presence of a 238 bp DNA fragment. The results of the phylogenetic analysis showed that the study sample formed a separate cluster from the E. bovis cluster from abroad. In conclusion, E. bovis was detected in 16 out of 18 provinces in this study, and the nPCR technique proved to have better sensitivity and specificity.
Related Topics
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.4308/hjb.31.5.980-987
- OA Status
- gold
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- OpenAlex ID
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Raw OpenAlex JSON
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https://openalex.org/W4400516185Canonical identifier for this work in OpenAlex
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https://doi.org/10.4308/hjb.31.5.980-987Digital Object Identifier
- Title
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Molecular Detection of Eimeria bovis in Indonesian Beef Cattle Using Nested PCR TechniqueWork title
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articleOpenAlex work type
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enPrimary language
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2024Year of publication
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2024-06-19Full publication date if available
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Mukh Fajar Nasrulloh, Wisnu Nurcahyo, Dwi Priyowidodo, Fitrine Ekawasti, Lintang Winantya FirdausyList of authors in order
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https://doi.org/10.4308/hjb.31.5.980-987Publisher landing page
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goldOpen access status per OpenAlex
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https://doi.org/10.4308/hjb.31.5.980-987Direct OA link when available
- Concepts
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Nested polymerase chain reaction, Biology, Beef cattle, Polymerase chain reaction, Veterinary medicine, Animal science, Genetics, Gene, MedicineTop concepts (fields/topics) attached by OpenAlex
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0Total citation count in OpenAlex
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.DNA | 171 |
| abstract_inverted_index.KIT | 93 |
| abstract_inverted_index.PCR | 46 |
| abstract_inverted_index.The | 75, 173 |
| abstract_inverted_index.and | 25, 32, 47, 80, 95, 107, 122, 143, 210, 219 |
| abstract_inverted_index.can | 13 |
| abstract_inverted_index.for | 140, 151, 160 |
| abstract_inverted_index.out | 133, 203 |
| abstract_inverted_index.the | 49, 82, 87, 98, 146, 165, 176, 181, 189, 211 |
| abstract_inverted_index.two | 117 |
| abstract_inverted_index.was | 199 |
| abstract_inverted_index.MEGA | 111 |
| abstract_inverted_index.This | 37, 114 |
| abstract_inverted_index.aims | 39 |
| abstract_inverted_index.beef | 60 |
| abstract_inverted_index.from | 66, 125, 188, 193 |
| abstract_inverted_index.have | 216 |
| abstract_inverted_index.many | 130 |
| abstract_inverted_index.nPCR | 99, 212 |
| abstract_inverted_index.spp. | 153 |
| abstract_inverted_index.that | 6, 180 |
| abstract_inverted_index.then | 81 |
| abstract_inverted_index.this | 208 |
| abstract_inverted_index.used | 116 |
| abstract_inverted_index.were | 63, 77, 84, 103, 138, 149, 155 |
| abstract_inverted_index.with | 51 |
| abstract_inverted_index.(50%) | 154 |
| abstract_inverted_index.ITS-1 | 126 |
| abstract_inverted_index.based | 163 |
| abstract_inverted_index.bovis | 1, 43, 162, 191, 198 |
| abstract_inverted_index.cause | 14 |
| abstract_inverted_index.farms | 68 |
| abstract_inverted_index.feces | 62, 76 |
| abstract_inverted_index.pairs | 118 |
| abstract_inverted_index.spp., | 142 |
| abstract_inverted_index.study | 38, 115, 182 |
| abstract_inverted_index.sugar | 88 |
| abstract_inverted_index.taken | 64, 124 |
| abstract_inverted_index.total | 55 |
| abstract_inverted_index.tract | 10 |
| abstract_inverted_index.using | 110 |
| abstract_inverted_index.which | 12 |
| abstract_inverted_index.(outer | 121 |
| abstract_inverted_index.across | 70 |
| abstract_inverted_index.better | 217 |
| abstract_inverted_index.cattle | 8, 61 |
| abstract_inverted_index.causes | 7 |
| abstract_inverted_index.detect | 41 |
| abstract_inverted_index.formed | 184 |
| abstract_inverted_index.inner) | 123 |
| abstract_inverted_index.losses | 16 |
| abstract_inverted_index.nested | 45 |
| abstract_inverted_index.proved | 214 |
| abstract_inverted_index.sample | 183 |
| abstract_inverted_index.showed | 179 |
| abstract_inverted_index.spread | 69 |
| abstract_inverted_index.study, | 209 |
| abstract_inverted_index.(57.5%) | 137 |
| abstract_inverted_index.Eimeria | 0, 141, 152 |
| abstract_inverted_index.abroad. | 194 |
| abstract_inverted_index.cluster | 187, 192 |
| abstract_inverted_index.develop | 23 |
| abstract_inverted_index.method, | 90 |
| abstract_inverted_index.methods | 28 |
| abstract_inverted_index.oocysts | 83 |
| abstract_inverted_index.prevent | 33 |
| abstract_inverted_index.primers | 120 |
| abstract_inverted_index.results | 174 |
| abstract_inverted_index.samples | 58, 102, 136, 148 |
| abstract_inverted_index.Positive | 101 |
| abstract_inverted_index.accurate | 26 |
| abstract_inverted_index.analysis | 109, 178 |
| abstract_inverted_index.conserve | 30 |
| abstract_inverted_index.detected | 156, 200 |
| abstract_inverted_index.economic | 15 |
| abstract_inverted_index.examined | 78 |
| abstract_inverted_index.farmers. | 18 |
| abstract_inverted_index.followed | 104 |
| abstract_inverted_index.markers. | 128 |
| abstract_inverted_index.positive | 139, 150, 159 |
| abstract_inverted_index.presence | 166 |
| abstract_inverted_index.purified | 85 |
| abstract_inverted_index.randomly | 65 |
| abstract_inverted_index.separate | 186 |
| abstract_inverted_index.specific | 24 |
| abstract_inverted_index.amplified | 96 |
| abstract_inverted_index.community | 67 |
| abstract_inverted_index.detection | 27 |
| abstract_inverted_index.determine | 48 |
| abstract_inverted_index.digestive | 9 |
| abstract_inverted_index.extracted | 91 |
| abstract_inverted_index.flotation | 89 |
| abstract_inverted_index.fragment. | 172 |
| abstract_inverted_index.livestock | 31 |
| abstract_inverted_index.molecular | 127 |
| abstract_inverted_index.natively, | 79 |
| abstract_inverted_index.necessary | 21 |
| abstract_inverted_index.protozoan | 5 |
| abstract_inverted_index.provinces | 72, 206 |
| abstract_inverted_index.reference | 52 |
| abstract_inverted_index.software. | 113 |
| abstract_inverted_index.technique | 213 |
| abstract_inverted_index.Indonesia. | 36, 74 |
| abstract_inverted_index.pathogenic | 4 |
| abstract_inverted_index.sequences. | 53 |
| abstract_inverted_index.sequencing | 106 |
| abstract_inverted_index.technique. | 100 |
| abstract_inverted_index.coccidiosis | 34 |
| abstract_inverted_index.conclusion, | 196 |
| abstract_inverted_index.extraction, | 94 |
| abstract_inverted_index.infections, | 11 |
| abstract_inverted_index.sensitivity | 218 |
| abstract_inverted_index.phylogenetic | 108, 177 |
| abstract_inverted_index.relationship | 50 |
| abstract_inverted_index.specificity. | 220 |
| cited_by_percentile_year | |
| countries_distinct_count | 1 |
| institutions_distinct_count | 5 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/2 |
| sustainable_development_goals[0].score | 0.550000011920929 |
| sustainable_development_goals[0].display_name | Zero hunger |
| citation_normalized_percentile.value | 0.1403772 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |