| Literature DB >> 35038109 |
Ehsan Ahmadpour1,2, Mohamad Taghi Rahimi3, Altin Ghojoghi4, Fatemeh Rezaei5, Kareem Hatam-Nahavandi6, Sónia M R Oliveira7,8, Maria de Lourdes Pereira7,9, Hamidreza Majidiani10, Abolghasem Siyadatpanah11, Samira Elhamirad12, Wei Cong13, Abdol Sattar Pagheh14.
Abstract
PURPOSE: Many marine animals are infected and susceptible to toxoplasmosis, which is considered as a potential transmission source of Toxoplasma gondii to other hosts, especially humans. The current systematic review and meta-analysis aimed to determine the prevalence of T. gondii infection among sea animal species worldwide and highlight the existing gaps.Entities:
Keywords: Marine animals; Meta-analysis; Systematic review; Toxoplasma gondii; Toxoplasmosis
Mesh:
Substances:
Year: 2022 PMID: 35038109 PMCID: PMC8761968 DOI: 10.1007/s11686-021-00507-z
Source DB: PubMed Journal: Acta Parasitol ISSN: 1230-2821 Impact factor: 1.534
Fig. 1Flowchart describing the study design process
Fig. 2Pooled prevalence of T. gondii in marine animal species in different continents
Detection of Toxoplasma gondii in marine animals (sorted by scientific name and publication date)
| Species | Location | Continent | Test | Sample size | Positive (%) | References |
|---|---|---|---|---|---|---|
| Dolphin | ||||||
| USA | North America | MAT | 141 | 138 (97.9) | Dubey | |
| | Australia | Australia | IHC | 4 | 4 (100) | Bowater |
| | Spain | Europe | MAT | 36 | 4 (11.1) | Cabezón et al [ |
| | Spain | Europe | MAT | 4 | 2 (50) | Cabezón |
| | Spain | Europe | MAT | 7 | 4 (57.1) | Cabezón |
| | Spain | Europe | MAT | 1 | 1 (100) | Cabezón |
| | Spain | Europe | MAT | 9 | 0 | Cabezón |
| | Solomon Islands | Oceania | Immunoblotting | 58 | 8 (13.8) | Omata |
| | Russia | Europe | ELISA | 59 | 27 (45.7) | Alekseev |
| | USA | North America | MAT | 52 | 27 (51.9) | Dubey |
| | Russia | Europe | ELISA | 74 | 39 (52.7) | Alekseev |
| | USA | North America | MAT | 7 | 7 (100) | Dubey |
| | United Kingdom | Europe | Sabin Feldman | 21 | 6 (28.5) | Forman |
| | United Kingdom | Europe | Sabin Feldman | 1 | 0 | Forman |
| | United Kingdom | Europe | Sabin Feldman | 1 | 0 | Forman |
| | United Kingdom | Europe | Sabin Feldman | 1 | 0 | Forman |
| | United Kingdom | Europe | Sabin Feldman | 5 | 0 | Forman |
| | Italy | Europe | IFA | 8 | 4 (50) | Di Guardo |
| | Italy | Europe | Nested-PCR and MAT | 8 | 7 (87.5) | Pretti |
| | Italy | Europe | Nested-PCR and MAT | 6 | 6 (100) | Pretti |
| | Brazil | South America | MAT | 95 | 82 (86.3) | Santos |
| | Mexico | North America | MAT | 63 | 55 (87.3) | Alvarado-Esquivel |
| | Mexico | North America | MAT | 3 | 3 (100) | Alvarado-Esquivel |
| | New Zealand | Oceania | PCR | 49 | 17 (34.7) | Roe |
| | Spain | Europe | IFA | 24 | 2 (8.3) | Bernal-Guadarrama |
| | Italy | Europe | IFA | 18 | 8 (44.4) | Profeta |
| | Italy | Europe | IFA | 3 | 2 (66.6) | Profeta |
| | Scotland | Europe | IFA | 7 | 2 (28.5) | |
| | Scotland | Europe | IFA | 13 | 2 (15.4) | van de Velde |
| | Scotland | Europe | IFA | 9 | 0 | van de Velde |
| | Scotland | Europe | IFA | 6 | 1 (16.6) | van de Velde |
| | Italy | Europe | PCR | 10 | 6 (60) | Pintore |
| | Italy | Europe | PCR | 1 | 1 (100) | Pintore |
| | Brazil | South America | IHC | 3 | 0 | Costa-Silva |
| | Brazil | South America | IHC | 2 | 0 | Costa-Silva |
| | Brazil | South America | IHC | 27 | 1 (3.7) | Costa-Silva |
| | Brazil | South America | IHC | 4 | 1 (25) | Costa-Silva |
| | Brazil | South America | IHC | 102 | 0 | Costa-Silva |
| | Brazil | South America | IHC | 6 | 0 | Costa-Silva |
| | Brazil | South America | IHC | 5 | 0 | Costa-Silva |
| | Brazil | South America | IHC | 6 | 0 | Costa-Silva |
| | Brazil | South America | IHC | 2 | 0 | Costa-Silva |
| Brazil | South America | IHC | 1 | 0 | Costa-Silva | |
| | Brazil | South America | IHC | 1 | 0 | Costa-Silva |
| | Brazil | South America | IHC | 1 | 0 | Costa-Silva |
| Whale | ||||||
| | Norway | Europe | MAT | 202 | 0 | Oksanen |
| | USA | North America | MAT | 3 | 0 | Dubey |
| | Spain | Europe | MAT | 1 | 0 | Cabezón |
| | Japan | Asia | PCR | 8 | 1 (12.5) | Omata |
| | Russia | Europe | ELISA | 147 | 7 (4.7) | Alekseev |
| | United Kingdom | Europe | Sabin Feldman | 1 | 1 (100) | Forman |
| | United Kingdom | Europe | Sabin Feldman | 1 | 0 | Forman |
| | Portugal | Europe | qPCR | 5 | 0 | Hermosilla |
| | Italy | Europe | IFA | 1 | 0 | van de Velde |
| | Italy | Europe | IFA | 1 | 0 | van de Velde |
| | Scotland | Europe | IFA | 1 | 0 | van de Velde |
| | Scotland | Europe | IFA | 3 | 0 | van de Velde |
| | Scotland | Europe | IFA | 10 | 4 (40) | van de Velde |
| | Scotland | Europe | IFA | 5 | 0 | van de Velde |
| | Scotland | Europe | IFA | 4 | 0 | van de Velde |
| | Scotland | Europe | IFA | 2 | 0 | Alekseev |
| | Scotland | Europe | IFA | 1 | 0 | Iqbal |
| | Russia | Europe | ELISA | 87 | 10 (11.5) | Profeta |
| | Canada | North America | PCR | 34 | 15 (44.1) | Profeta |
| | Italy | Europe | PCR | 1 | 0 | Pintore |
| | Brazil | South America | IHC | 7 | 0 | Costa-Silva |
| | Brazil | South America | IHC | 5 | 0 | Costa-Silva |
| | Brazil | South America | IHC | 3 | 0 | Costa-Silva |
| | Brazil | South America | IHC | 3 | 0 | Costa-Silva |
| Brazil | South America | IHC | 2 | 0 | Costa-Silva | |
| | Brazil | South America | IHC | 2 | 0 | Costa-Silva |
| | Brazil | South America | IHC | 2 | 1 (50) | Costa-Silva |
| | Brazil | South America | IHC | 1 | 0 | Costa-Silva |
| | Italy | Europe | PCR | 7 | 1 (14.2) | Marcer |
| Seals | ||||||
| Norway | Europe | MAT | 316 | 0 | Oksanen | |
| Norway | Europe | MAT | 48 | 0 | Oksanen | |
| Norway | Europe | MAT | 78 | 0 | Oksanen | |
| USA | North America | MAT | 380 | 29 (7.6) | Lambourn | |
| USA | North America | MAT | 311 | 51 (16.4) | Dubey | |
| USA | North America | MAT | 32 | 5 (15.6) | Dubey | |
| USA | North America | MAT | 8 | 4 (50) | Dubey | |
| USA | North America | MAT | 9 | 1 (11.1) | Dubey | |
| USA | North America | MAT | 14 | 0 | Dubey | |
| Canada | North America | MAT | 112 | 0 | Measures | |
| Canada | North America | MAT | 60 | 1 (1.6) | Measures | |
| Canada | North America | MAT | 122 | 11 (9) | Measures | |
| Canada | North America | MAT | 34 | 3 (8.8) | Measures | |
| Japan | Asia | ELISA | 77 | 3 (3.9) | Fujii | |
| Spain | Europe | MAT | 56 | 3 (5.3) | Cabezón | |
| Spain | Europe | MAT | 47 | 11 (23.4) | Cabezón | |
| Canada | North America | DAT | 788 | 80 (10.1) | Simon | |
| Canada | North America | DAT | 20 | 2 (10) | Simon | |
| Canada | North America | DAT | 9 | 2 (22.2) | Simon | |
| Antarctic Peninsula | South America | DAT | 31 | 13 (41.9) | Rengifo-Herrera | |
| Antarctic Peninsula | South America | DAT | 13 | 10 (76.9) | Rengifo-Herrera | |
| Antarctic Peninsula | South America | DAT | 2 | 1 (50) | Rengifo-Herrera | |
| Antarctic Peninsula | South America | DAT | 165 | 4 (2.4) | Rengifo-Herrera | |
| Antarctica | Antarctica | DAT | 21 | 12 (57.1) | Jensen | |
| Antarctica | Antarctica | DAT | 33 | 17 (51.5) | Jensen | |
| Antarctica | Antarctica | DAT | 48 | 11 (22.9) | Jensen | |
| | Peru | South America | IFA | 27 | 0 | Jankowski |
| | Scotland | Europe | IFA | 13 | 0 | van de Velde |
| Scotland | Europe | IFA | 17 | 2 (11.7) | van de Velde | |
| Alaska | North America | IFA | 34 | 0 | Bauer | |
| Iran | Asia | MAT | 36 | 30 (83.3) | Namroodi | |
| Sea lions | ||||||
| | USA | North America | MAT | 45 | 19 (42.2) | Dubey |
| | Mexico | North America | MAT | 2 | 0 | Alvarado-Esquivel |
| | Mexico | North America | MAT | 4 | 2 (50) | Alvarado-Esquivel |
| | USA | North America | IFA | 1630 | 46 (2.8) | Carlson-Bremer |
| | New Zealand | Oceania | ELISA | 50 | 5 (10) | Michael |
| Sea otters | ||||||
| | USA | North America | LAT | 103 | 46 (44.6) | Tocidlowski |
| | USA | North America | IFA | 223 | 115 (51.5) | Miller |
| | USA | North America | IFA | 80 | 29 (36.2) | Miller |
| | USA | North America | IFA | 21 | 8 (38.1) | Miller |
| | USA | North America | IFA | 65 | 0 | Miller |
| | USA | North America | Microscopic test | 35 | 15 (42.8) | Miller |
| | USA | North America | MAT | 145 | 107 (73.7) | Dubey |
| | USA | North America | IFA | 40 | 7 (17.5) | Gaydos |
| | Scotland | Europe | IFA | 32 | 17 (53.1) | van de Velde |
| | USA | North America | MAT | 70 | 65 (92.8) | Verma |
| Porpoise | ||||||
| | United Kingdom | Europe | Sabin Feldman | 70 | 1 (1.4) | Forman |
| | Netherlands | Europe | MAT | 31 | 4 (12.9) | van de Velde |
| | Scotland | Europe | IFA | 98 | 2 (2) | van de Velde |
| Oysters/mussels/shellfish | ||||||
| | Brazil | South America | Nested PCR | 300 | 0 | Esmerini |
| | Brazil | South America | Nested PCR | 300 | 10 (3.3) | Esmerini |
| | Turkey | Europe | HRM | 53 | 21 (39.6) | Aksoy |
| | China | Asia | PCR | 398 | 0 | Zhang |
| | Italy | Europe | qPCR | 53 | 7 (13.2) | Marangi |
| | USA | North America | PCR | 230 | 4 (1.7) | Marquis |
| | Brazil | South America | PCR | 624 | 17 (2.7) | Ribeiro |
| Oysters | China | Asia | Nested PCR | 998 | 26 (2.6) | Cong |
| | New Zealand | Oceania | Nested PCR | 104 | 13 (12.5) | Coupe |
| | China | Asia | Nested PCR | 2215 | 55 (2.4) | Cong |
| | USA | North America | qPCR | 1440 | 446 (30.9) | Marquis |
| Fishes | ||||||
| | China | Asia | PCR | 309 | 0 | Zhang |
| | China | Asia | PCR | 309 | 0 | Zhang |
| | China | Asia | PCR | 456 | 1 (0.2) | Zhang |
| Fishes | Italy | Europe | qPCR | 147 | 32 (21.7) | Marino |
| Shrimp | ||||||
| | China | Asia | PCR | 426 | 0 | Zhang |
| | China | Asia | PCR | 813 | 1 (0.1) | Zhang |
| Manatees | ||||||
| | Mexico | North America | MAT | 3 | 0 | Alvarado-Esquivel |
| | MAT | 74 | 29 (39.1) | Mathews | ||
| Walruses | ||||||
| | USA | North America | MAT | 53 | 3 (5.6) | Dubey |
| Eel | ||||||
| | China | Asia | PCR | 98 | 0 | Zhang |
| Crayfish | ||||||
| | China | Asia | PCR | 618 | 4 (0.64) | Zhang |
IHC immunohistochemistry, IFA immunofluorescence antibody test, DAT direct agglutination test, LAT latex agglutination test, HRM real time PCR/high-resolution melting analysis, IHAT indirect hemagglutination test
Pooled prevalence of Toxoplasma infection in marine animals and subgroup analyses
| Types of animals (species) | No. of studies | Prevalence (95% CI) | Heterogeneity | Egger’s test | |||
|---|---|---|---|---|---|---|---|
| 36 | 30.92 (17.85–45.76) | 97.5 | 1377.98 | < 0.0001 | 4.87 | 0.0489 | |
| 18 | 12.16 (7.28–18.09) | 96.3 | 460.63 | < 0.0001 | 4.59 | 0.0004 | |
| 2 | 26.51 (2.46–63.69) | – | 2.62 | 0.1049 | – | – | |
| 6 | 54.8 (34.21–74.57) | 96.6 | 147.12 | < 0.0001 | −0.42 | 0.9593 | |
| 5 | 1.64 (0.02–7.22) | 96.2 | 105.71 | < 0.0001 | 4.34 | 0.1065 | |
| 3 | 0.26 (0.03–0.73) | 57.1 | 4.35 | 0.1132 | – | – | |
| 10 | 7.45 (2.06–15.81) | 99.1 | 962.83 | < 0.0001 | 7.56 | 0.067 | |