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Natural infection of Phlebotomus argentipes with Leishmania and other trypanosomatids in a visceral leishmaniasis endemic region of Nepal
Transactions of the Royal Society of Tropical Medicine and Hygiene (2009) 103, 1087—1092
available at www.sciencedirect.com
journal homepage: http://www.elsevier.com/locate/trstmh
Natural infection of Phlebotomus argentipes with Leishmania and other trypanosomatids in a visceral leishmaniasis endemic region of Nepal Narayan Raj Bhattarai a,b,c, Murari Lal Das b, Suman Rijal b, Gert van der Auwera a, Albert Picado d, Basudha Khanal b, Lalita Roy b, Niko Speybroeck a,e, Dirk Berkvens a, Clive R. Davies d,, Marc Coosemans a, Marleen Boelaert a, Jean-Claude Dujardin a,c,∗ a
Departments of Parasitology, Public Health and Veterinary and Animal Sciences, Institute of Tropical Medicine, Antwerpen, Belgium b B.P. Koirala Institute of Health Sciences, Dharan, Nepal c Department of Biomedical Science, University of Antwerpen, Antwerpen, Belgium d London School of Hygiene and Tropical Medicine, London, UK e Ecole de Santé Publique, Université Catholique de Louvain, Louvain-la-Neuve, Belgium Received 12 December 2008; received in revised form 9 March 2009; accepted 9 March 2009 Available online 3 April 2009
KEYWORDS Leishmania; Phlebotomus argentipes; PCR; Kala-azar; Ribosomal DNA; Nepal
Summary Monitoring Leishmania infection in sand flies is important for understanding the eco-epidemiology of kala-azar and assessing the impact of the recently launched kala-azar control programme in the Indian subcontinent. We applied a PCR technique that targets rRNA genes to estimate the natural incidence of Leishmania infection in sand flies sampled in six villages of the Terai region of Nepal. Amplifications were made on 135 pools of sand flies and confirmed by sequencing. Seven pools were found to be PCR positive: in five of them we identified the rDNA signature found in Leishmania spp., whereas two other pools revealed a sequence compatible with other trypanosomatids. Different methodologies were applied to evaluate the infection rate from pools of unequal size and estimated the infection rate to range from 0.468% to 0.578% for the Leishmania group and from 0.185% to 0.279% for the non-Leishmania group. Our results highlight the diversity of flagellate infections likely to be encountered in Phlebotomus argentipes populations. Our methodology allows clear discrimination of Leishmania from other trypanosomatids and should be applied on larger insect samples or in longitudinal studies. © 2009 Royal Society of Tropical Medicine and Hygiene. Published by Elsevier Ltd. All rights reserved.
∗
Corresponding author. Tel.: +32 324 76358; fax: +32 324 76359. E-mail address: [email protected] (J.-C. Dujardin). Deceased. 0035-9203/$ — see front matter © 2009 Royal Society of Tropical Medicine and Hygiene. Published by Elsevier Ltd. All rights reserved. doi:10.1016/j.trstmh.2009.03.008
1088
1. Introduction In the Indian subcontinent, visceral leishmaniasis (VL) is considered to be a major public health problem and the case load in this region accounts for 60% of the global burden of the disease. The disease is caused by Leishmania donovani, which is transmitted by the bite of infected female sand flies of the species Phlebotomus argentipes.1 In 2005, the governments of Bangladesh, India and Nepal signed an agreement for a regional VL elimination plan, based on active surveillance for disease and vector, early diagnosis, complete treatment, vector control through integrated vector management, social mobilization of the population at risk and partnership, networking and operational research.2 The monitoring of natural Leishmania infection in sand fly populations is an important element of surveillance, the prediction of risk and prevalence of disease, and for evaluating the impact of control programmes, among others. In this context, different PCR-based techniques are now available for the mass screening of vector populations. However, most techniques are applied either in individual sand flies3,4 or in sand fly pools of fixed sizes.5,6 Due to the low Leishmania infection rate in sand flies,7 estimation at the individual level can be cumbersome. In turn, the assessment of fixed pool sizes may take longer and always reduces the possibility of analyzing important information at a household level, such as the ecology of trap placement etc, since sand fly captures in the field do not produce homogeneous sample sizes. In the present study we applied a highly sensitive PCR assay targeting the rRNA genes of Leishmania8 and used a statistical method based on variable pool size to estimate the natural Leishmania infection rate in sand flies from a VL endemic region of Nepal.
2. Materials and methods 2.1. Study background The study was undertaken within the framework of the KALANET project,9 a community trial to assess the effectiveness of long-lasting insecticide-impregnated bed nets to prevent VL infection.
2.2. Study area The study was conducted in Sunsari district, a VL endemic area in eastern Nepal, characterized by an incidence of VL ≥45/100 000 per year during the period 2001—2006.10 Of ten wards (a ward is an administrative division corresponding to a subunit of a village, usually 350—1500 persons) included in the KALANET project, six were selected for the present study: Amahibelha, Aurabani, Bhokraha, Dharan-17, Duhabi and Tanmuna (Figure 1).
N.R. Bhattarai et al. numbered. In order to determine sand fly density, flies were collected for 10 min in each household; this was performed by trained fieldworkers, using the mouth aspiration method. In a second step, the 10 households from each ward showing the highest number of Phlebotomus argentipes were then selected. Thus, a total of 60 houses and their cattle sheds were selected from the six wards (if the household had no cattle shed then the cattle shed of the neighbour). These were monitored monthly for 15 months, from September 2006 to November 2007. The number of pools in each ward is shown in Table 1. Among the 60 selected households, the indoor density of sand flies was monitored with CDC light traps11 set up from 6 p.m. to 6 a.m., followed by mouth aspiration for 15 min; in cattle sheds, only mouth aspiration for 15 min was used. The insects were brought to the entomology laboratory at the B.P. Koirala Institute of Health Sciences, Dharan, Nepal, examined under a binocular dissecting microscope and female P. argentipes morphologically identified and separated from other insects.12 Female P. argentipes were pooled by household and by month in a cryotube with 80% alcohol. Specimens from indoor household collection and cattle sheds were kept in separate tubes.
2.4. Molecular analyses All the pools of insects were sent to the Institute of Tropical Medicine, Antwerp, Belgium for further analysis. DNA was extracted by the High Pure PCR Template Preparation Kit (Roche, Mannheim, Germany), as per the manufacturer’s instructions. Firstly, a PCR assay was applied to verify the quality of the DNA present in each pool and exclude possible inhibitors. For this purpose, a 500 bp fragment of the sand fly cytochrome b gene was amplified with the primers CB1 and CB3-R3A.13 In a second step to determine Leishmania infection, all the cytochrome b PCR-positive pools were analysed by PCR assay targeting the small subunit rRNA genes of Leishmania, previously shown to be able to detect one parasite in 180 l of blood and 10 fg purified DNA (equivalent to 0.05 parasite genomes).8 Negative samples were submitted to a new amplification, using 1/10 dilution of template DNA to decrease potential inhibitor. Positive and negative controls were included in each PCR run. The two positive controls consisted of 1 ng and 0.1 pg of L. donovani (MHOM/NP/03/BPK206/0) DNA, while DNA-free Milli-Q Plus PF water (Millipore, Bedford, MA, USA) was included as the negative control. In addition, DNA extracted from a Leishmania-infected sand fly was also included in each run of PCR as another positive control. In order to confirm that the amplified DNA corresponded well to Leishmania, amplicons were sequenced (3730 DNA Analyzer, Applied Biosystems, Foster City, CA, USA) using the forward and reverse primer. The results were compared with Leishmania sequences from GenBank.
2.5. Statistical methods 2.3. Entomological procedures The identification of houses for sand fly collection was performed in two steps. In the first step, 25 households were randomly selected from each of the six wards, each household in a ward having previously been mapped and
Two methods were used for computing the prevalence of parasite infection in pools of unequal size: the simulation method14 using R (http://cran.r-project.org) and the Farrington method15 using Stata 10 (Stata Corp., College Station, TX, USA). The simulation method uses
Natural infection of Phlebotomus argentipes with Leishmania
Figure 1
1089
Location of the study area in the Sunsari district, Nepal. BPKIHS: B.P. Koirala Institute of Health Sciences.
repeated, randomly generated samples of sand flies with specific prevalence. Each time the prevalence results in the observed number of positive pools, it is stored in the list. The list represents the distribution of possible prevalence. Once the size of the list is sufficient, it can be used to calculate the required quantiles for summarizing the distribution, resulting in confidence intervals. By contrast, the Farrington method uses generalized linear modelling, with a binomial family and a complementary log-log link to calculate the maximum-likelihood estimates of prevalence and confidence limit, when multiple different pool sizes are used. In addition to providing prevalence estimates and con-
fidence intervals, the approach can be used to regress the prevalence on covariates. Comparing the simulations with the results of the generalized linear model indicated that in some instances (i.e. when the sample sizes or pool sizes are small), the result can be different when using two methods. For the sand fly data, we checked whether the two methods provided different results and, if so, reported the difference. If the results were similar, we reported the results of the generalized linear model. The infection rate was calculated by the method of pooled prevalence for variable pool size and perfect tests (assuming 100% sensitivity and specificity).
1090 Table 1
N.R. Bhattarai et al. Origin and distribution of sand fly pools
Wards
Amahibelha Aurabani Bhokraha Dharan-17b Duhabi Tanmuna Total a b
Indoor household collection
Cattle shed collection
No. of pools collected
No. of pools collected
No. of PCR-positive pools
No. of PCR-positive pools
21 9 10 12 49 18
0 1+1a = 2 0 0 1 2+1a = 3
6 1 1 1 5 1
0 0 0 0 1 0
119
4+2a = 6
15
1
Non-Leishmania type, as revealed by sequencing. One pool was PCR negative for the sand fly cytochrome b gene and was excluded from the table.
3. Results
4. Discussion
A total of 135 pools were prepared, each containing 1—20 insects (in total 1084 insects): 120 pools were from indoor household collections and 15 pools were from cattle sheds. All but one pool were found to be PCR positive for the cytochrome b gene, indicating the good quality of DNA in these samples. Seven of these pools were found to be positive by the PCR assay targeting the rRNA genes of Leishmania. Sequencing of the corresponding amplicons showed, in five of the seven pools, the rDNA signature encountered among all Leishmania species, including L. donovani, the main species circulating in the Indian subcontinent. However, the two other pools revealed a slightly different sequence, with a signature compatible with Endotrypanum spp., Leptomonas costaricensis, Sauroleishmania tarentolae or trypanosomatids isolated from immunodepressed patients from Martinique. For simplicity, the parasites encountered in the latter two pools are further referred to as non-Leishmania. The five Leishmania-positive pools were distributed as follows (Table 1): two from Duhabi, one of them from a cattle-shed, and three from Aurabani and Tanmuna, all originating from indoor household collection. Both nonLeishmania infected pools were collected inside households in the same wards as Leishmania-positive pools, that is, Aurabani and Tanmuna. The infection rate was computed by two methods. Using the simulation method, we estimated a rate of 0.578% (95% CI 0.218—1.111) for Leishmania and 0.279% (95% CI 0.060—0.685) for non-Leishmania infection. With the Farrington method, we estimated 0.468% (95% CI 0.195—1.122) for Leishmania and 0.185% (95% CI 0.0463—0.733) for non-Leishmania infection. Since the Farrington method can be used only with sufficient positive pools of adequate size, the ward-wise estimation of Leishmania and non-Leishmania infection rates was only made by the simulation method. Results were distributed as follows for Leishmania: Aurabani: 5.727% (95% CI 0.766—15.047); Tanmuna: 2.711% (95% CI 0.609—6.214) and Duhabi: 0.505% (95% CI 0.108—1.155). With respect to non-Leishmania infections, we found the following: Aurabani: 5.701% (95% CI 0.727—15.26) and Tanmuna: 1.681% (95% CI 0.200—4.480).
We showed the presence of Leishmania as well as other trypanosomatids in the P. argentipes specimens collected in the study area. Depending on the method used, we estimated an infection rate of 0.468—0.578% for Leishmania spp. and 0.185—0.279% for non-Leishmania spp. over the whole study area. Of note, these estimations apply to samples captured in households of wards selected by the KALANET project as having the highest transmission in the past 3 years. Accordingly, they do not necessarily represent the infection rate in the whole endemic region. Nonetheless, our estimation of Leishmania infection rates over the whole area is close to values reported in the neighbouring Indian state of Bihar (0.1%, as estimated by dissection)16 and in Spain (0.027—0.45%, as estimated by PCR-ELISA),5 but different from those reported in Ecuador (3.3%),17 Greece (6.4%)18 and another district of Nepal (6.7%).3 Comparison between studies should be made with extreme care, as transmission features may differ and sampling and experimental protocols are not standardized among these studies. For instance, in the study performed by Pandey et al. in Nepal,3 a smaller sample size was considered (401 insects), individual insects were used instead of pools, samples were collected from five villages instead of six villages, a different and possibly more sensitive PCR assay targeting kDNA was applied, and no statistical methods were considered. Furthermore, a sampling bias could not be excluded in that report. For example, if sampling had been concentrated in a few houses characterized by intensive transmission, that is, many sand flies feeding on the same infected host. This is supported in the present study by estimating infection rates at ward level; in some wards, like Duhabi, a 0.505% infection rate was estimated, while in others, like Aurabani, a rate of 5.727% was estimated. In addition, the authors are likely to have overestimated the infection rate by counting positive amplifications in which the identity of Leishmania was not confirmed. The present study showed that this could be a problem, as non-Leishmania infections were also observed in P. argentipes, sometimes in the same wards (Aurabani and Tanmuna). We could not further elucidate the identity of these other parasites. They were possibly Leptomonas spp.,
Natural infection of Phlebotomus argentipes with Leishmania Endotrypanum spp. or Sauroleishmania spp. (the two latter species have never been reported, to our knowledge, in the Indian subcontinent), or even a parasite similar to the trypanosomatid isolated from immunodepressed patients in Martinique and reported to branch at the base of the Leishmania cluster.19 Sand flies are well known to harbour other parasites than Leishmania: monogenic, like Crithidia species19 or digenic like Trypanosoma leonidasnei,20 flagellates generally not pathogenic for humans, except in rare cases of co-infection. Other studies performed by our group support this idea; despite an extensive survey in the region, we have not encountered this non-Leishmania type in asymptomatic humans21 or VL patients,8 and not in domestic animals either (N.R. Bhattarai, personal communication). With respect to sand fly infection rates with these non-Leishmania parasites, our estimates are lower than those reported from other epidemiological settings: 7.1% by Crithidia species in Panama22 and up to 42% by Trypanosoma leonidasnei in Belize.20 However, our PCR assay does not amplify all flagellates (e.g. T. brucei, T. cruzi8 or T. evansi; J.C. Dujardin, personal communication), hence the prevalence of non-Leishmania infections in sand flies could be underestimated. Further work should be done to identify the parasites isolated from our sand fly sample, but nonetheless our results highlight the need to complement natural infection rate studies with precise typing. The detection of Leishmania is highly relevant for the surveillance of VL and to support control activities. However, particular attention should also be given to non-Leishmania spp., as their precise identification might give indirect information on the behaviour of P. argentipes, the biology of which is still not perfectly understood. Authors’ note: This paper is dedicated to the memory of our colleague and friend, Clive Davies, who passed away in March 2009. Authors’ contributions: NRB, MLD, SR, GvdA, AP, BK, LR, NS, DB and MB contributed to the study design; CRD and MC designed the entomological aspects of the study; J-CD designed the molecular aspects of the study and developed the methods of analysis; MB supervised and coordinated the study; AP supervised and ensured quality control of the field work; SR selected and coordinated the field work; MLD and BK participated in the field work; MLD and LR collected and identified sand flies; NRB prepared the pools of sand files, extracted DNA, ran the PCR and analysed the data; NS and DB participated in the statistical analysis of the sand fly pools; GvdA was responsible for database management; All authors contributed to the preparation of the manuscript and J-CD wrote the final version. All authors read and approved the final manuscript. J-CD is guarantor of the paper. Acknowledgements: We would like to thank Dr Jan Vot´ ypka for his help in providing the DNA extraction protocol and infected sand fly for testing and validating the DNA extraction and control PCR techniques. In addition, our thanks go to all the field workers who helped to collect and process the sand flies in Nepal.
1091 Funding: EU-funded KALANET project (contract no. INCOCT 2005—01537). Conflicts of interest: None declared. Ethical approval: Ethical clearance to conduct the KALANET project was obtained from the ethical committee of the B.P. Koirala Institute of Health Sciences, Dharan, Nepal and the corresponding bodies at the Institute of Tropical Medicine, Antwerp, Belgium and the London School of Hygiene and Tropical Medicine, London, UK.
References 1. Dinesh DS, Kar SK, Kishore K, Palit A, Verma N, Gupta AK, et al. Screening sandflies for natural infection with Leishmania donovani, using a nonradioactive probe based on the total DNA of the parasite. Ann Trop Med Parasitol 2000;94: 447—51. 2. Joshi A, Narain JP, Prasittisuk C, Bhatia R, Hashim G, Jorge A, et al. Can visceral leishmaniasis be eliminated from Asia? Vector Borne Dis 2008;45:105—11. 3. Pandey K, Panta S, Kanbara H, Nasir Shuaibu M, Mallik AK, Pandey BD, et al. Molecular detection of Leishmania parasites from whole bodies of sandflies collected in Nepal. Parasitol Res 2008;103:293—7. 4. Kato H, Uezato H, Gomez EA, Terayama Y, Calvopi˜ na M, Iwata H, et al. Establishment of a mass screening method of sandfly vectors for Leishmania infection by molecular biological methods. Am J Trop Med Hyg 2007;77:324—9. 5. Martın-Sanchez J, Gˇıallego M, Barˇıon S, Castillejo S, MorillasMarquez F. Pool Screen PCR for estimating the prevalence of Leishmania infantum in sandflies (Diptera: Nematocera, Phlebotomidae). Trans R Soc Trop Med Hyg 2006;100:527—32. 6. Carvalho GML, Andrade Filho JD, Falcao AL, Rocha Lima ACVM, Gontigo CMF. Naturally infected Lutzomiya sandflies in a Leishmania-endemic area of Brazil. Vector Borne Zoonotic Dis 2008;8:407—14. 7. Killick-Kendrick R, Ward RD. Ecology of Leishmania. Parasitology 1981;82:143—52. 8. Deborggraeve S, Boelaert M, Rijal S, De Doncker S, Dujardin JC, Herdewijn P, et al. Diagnostic accuracy of a new Leishmania PCR for clinical visceral leishmaniasis in Nepal and its role in diagnosis of disease. Trop Med Int Health 2008;13:1378—83. 9. KALANET Project. http://www.kalanetproject.org [accessed 26 February 2009]. 10. Thapa LB, Banerjee MK, Thakur GD, Shrestha GM, Shakya GM, Thapa G, et al. The internal assessment of malaria and kala-azar control activities, 2004, 2005 and 2006. Teku, Kathmandu, Nepal: Department of Health Services, Epidemiology and Disease Control Division, Ministry of Health and Population; 2009. 11. Dinesh D, Das P, Picado A, Davies C, Speybroeck N, Boelaert M, et al. The efficacy of indoor CDC light traps for collecting the sand fly Phlebotomus argentipes, vector of Leishmania donovani. Med Vet Entomol 2008;22:120—3. 12. Lewis DJ. The phlebotomine sandflies (Diptera: Psychodidae) from the oriental region. Syst Entomol 1987;12:163— 80. 13. Esseghir S, Ready PD. Speciation of Phlebotomus sandflies of the subgenus Larroussius coincided with the late MiocenePliocene aridification of the Mediterranean subregion. Biol J Linn Soc Lond 2000;70:189—219. 14. Ihaka R, Gentleman R. A language for data analysis and graphics. J Comput Graph Stat 1996;5:299—314.
1092 15. Farrington CP. Estimating prevalence by group testing using generalized linear models. Stat Med 1992;11: 1591—7. 16. Kumar V, Kishore K, Palit A, Keshari S, Sharma MC, Das VN, et al. Vectorial efficacy of Phlebotomus argentipes in Kalaazar endemic foci of Bihar (India) under natural and artificial conditions. J Commun Dis 2001;33:102—9. 17. Kato H, Uezato H, Katakura K, Calvopi˜ na M, Marco JD, Barroso PA, et al. Detection and identification of Leishmania species within naturally infected sand flies in the Andean areas of Ecuador by a polymerase chain reaction. Am J Trop Med Hyg 2005;72:87—93. 18. Aransay AM, Scoulica E, Tselentis Y. Detection and identification of Leishmania DNA within naturally infected sand flies by seminested PCR on minicircle kinetoplastic DNA. Appl Environ Microbiol 2000;66:1933—8.
N.R. Bhattarai et al. 19. Noyes H, Pratlong F, Chance M, Ellis J, Lanotte G, Dedet JP. A previously unclassified trypanosomatid responsible for human cutaneous lesions in Martinique (French West Indies) is the most divergent member of the genus Leishmania ss. Parasitology 2002;124:17—24. 20. Williams P. Flagellate infections in cave-dwelling sandflies (Diptera, Psychodidae) in Belize, Central America. Bull Entomol Res 1976;65:615—29. 21. Bhattarai NR, Van der Auwera G, Rijal S, De Doncker S, Khanal B, Das ML, et al. PCR and direct agglutination as Leishmania infection markers among healthy Nepalese subjects living in areas endemic for Kala-Azar. Trop Med Int Health. Forthcoming 2009. 22. Wallace FG, Hertig M. Ultrastructural comparison of promastigote flagellates (leptomonads) of wild-caught Panamanian Phlebotomus. J Parasitol 1968;54:606—12.
available at www.sciencedirect.com
journal homepage: http://www.elsevier.com/locate/trstmh
Natural infection of Phlebotomus argentipes with Leishmania and other trypanosomatids in a visceral leishmaniasis endemic region of Nepal Narayan Raj Bhattarai a,b,c, Murari Lal Das b, Suman Rijal b, Gert van der Auwera a, Albert Picado d, Basudha Khanal b, Lalita Roy b, Niko Speybroeck a,e, Dirk Berkvens a, Clive R. Davies d,, Marc Coosemans a, Marleen Boelaert a, Jean-Claude Dujardin a,c,∗ a
Departments of Parasitology, Public Health and Veterinary and Animal Sciences, Institute of Tropical Medicine, Antwerpen, Belgium b B.P. Koirala Institute of Health Sciences, Dharan, Nepal c Department of Biomedical Science, University of Antwerpen, Antwerpen, Belgium d London School of Hygiene and Tropical Medicine, London, UK e Ecole de Santé Publique, Université Catholique de Louvain, Louvain-la-Neuve, Belgium Received 12 December 2008; received in revised form 9 March 2009; accepted 9 March 2009 Available online 3 April 2009
KEYWORDS Leishmania; Phlebotomus argentipes; PCR; Kala-azar; Ribosomal DNA; Nepal
Summary Monitoring Leishmania infection in sand flies is important for understanding the eco-epidemiology of kala-azar and assessing the impact of the recently launched kala-azar control programme in the Indian subcontinent. We applied a PCR technique that targets rRNA genes to estimate the natural incidence of Leishmania infection in sand flies sampled in six villages of the Terai region of Nepal. Amplifications were made on 135 pools of sand flies and confirmed by sequencing. Seven pools were found to be PCR positive: in five of them we identified the rDNA signature found in Leishmania spp., whereas two other pools revealed a sequence compatible with other trypanosomatids. Different methodologies were applied to evaluate the infection rate from pools of unequal size and estimated the infection rate to range from 0.468% to 0.578% for the Leishmania group and from 0.185% to 0.279% for the non-Leishmania group. Our results highlight the diversity of flagellate infections likely to be encountered in Phlebotomus argentipes populations. Our methodology allows clear discrimination of Leishmania from other trypanosomatids and should be applied on larger insect samples or in longitudinal studies. © 2009 Royal Society of Tropical Medicine and Hygiene. Published by Elsevier Ltd. All rights reserved.
∗
Corresponding author. Tel.: +32 324 76358; fax: +32 324 76359. E-mail address: [email protected] (J.-C. Dujardin). Deceased. 0035-9203/$ — see front matter © 2009 Royal Society of Tropical Medicine and Hygiene. Published by Elsevier Ltd. All rights reserved. doi:10.1016/j.trstmh.2009.03.008
1088
1. Introduction In the Indian subcontinent, visceral leishmaniasis (VL) is considered to be a major public health problem and the case load in this region accounts for 60% of the global burden of the disease. The disease is caused by Leishmania donovani, which is transmitted by the bite of infected female sand flies of the species Phlebotomus argentipes.1 In 2005, the governments of Bangladesh, India and Nepal signed an agreement for a regional VL elimination plan, based on active surveillance for disease and vector, early diagnosis, complete treatment, vector control through integrated vector management, social mobilization of the population at risk and partnership, networking and operational research.2 The monitoring of natural Leishmania infection in sand fly populations is an important element of surveillance, the prediction of risk and prevalence of disease, and for evaluating the impact of control programmes, among others. In this context, different PCR-based techniques are now available for the mass screening of vector populations. However, most techniques are applied either in individual sand flies3,4 or in sand fly pools of fixed sizes.5,6 Due to the low Leishmania infection rate in sand flies,7 estimation at the individual level can be cumbersome. In turn, the assessment of fixed pool sizes may take longer and always reduces the possibility of analyzing important information at a household level, such as the ecology of trap placement etc, since sand fly captures in the field do not produce homogeneous sample sizes. In the present study we applied a highly sensitive PCR assay targeting the rRNA genes of Leishmania8 and used a statistical method based on variable pool size to estimate the natural Leishmania infection rate in sand flies from a VL endemic region of Nepal.
2. Materials and methods 2.1. Study background The study was undertaken within the framework of the KALANET project,9 a community trial to assess the effectiveness of long-lasting insecticide-impregnated bed nets to prevent VL infection.
2.2. Study area The study was conducted in Sunsari district, a VL endemic area in eastern Nepal, characterized by an incidence of VL ≥45/100 000 per year during the period 2001—2006.10 Of ten wards (a ward is an administrative division corresponding to a subunit of a village, usually 350—1500 persons) included in the KALANET project, six were selected for the present study: Amahibelha, Aurabani, Bhokraha, Dharan-17, Duhabi and Tanmuna (Figure 1).
N.R. Bhattarai et al. numbered. In order to determine sand fly density, flies were collected for 10 min in each household; this was performed by trained fieldworkers, using the mouth aspiration method. In a second step, the 10 households from each ward showing the highest number of Phlebotomus argentipes were then selected. Thus, a total of 60 houses and their cattle sheds were selected from the six wards (if the household had no cattle shed then the cattle shed of the neighbour). These were monitored monthly for 15 months, from September 2006 to November 2007. The number of pools in each ward is shown in Table 1. Among the 60 selected households, the indoor density of sand flies was monitored with CDC light traps11 set up from 6 p.m. to 6 a.m., followed by mouth aspiration for 15 min; in cattle sheds, only mouth aspiration for 15 min was used. The insects were brought to the entomology laboratory at the B.P. Koirala Institute of Health Sciences, Dharan, Nepal, examined under a binocular dissecting microscope and female P. argentipes morphologically identified and separated from other insects.12 Female P. argentipes were pooled by household and by month in a cryotube with 80% alcohol. Specimens from indoor household collection and cattle sheds were kept in separate tubes.
2.4. Molecular analyses All the pools of insects were sent to the Institute of Tropical Medicine, Antwerp, Belgium for further analysis. DNA was extracted by the High Pure PCR Template Preparation Kit (Roche, Mannheim, Germany), as per the manufacturer’s instructions. Firstly, a PCR assay was applied to verify the quality of the DNA present in each pool and exclude possible inhibitors. For this purpose, a 500 bp fragment of the sand fly cytochrome b gene was amplified with the primers CB1 and CB3-R3A.13 In a second step to determine Leishmania infection, all the cytochrome b PCR-positive pools were analysed by PCR assay targeting the small subunit rRNA genes of Leishmania, previously shown to be able to detect one parasite in 180 l of blood and 10 fg purified DNA (equivalent to 0.05 parasite genomes).8 Negative samples were submitted to a new amplification, using 1/10 dilution of template DNA to decrease potential inhibitor. Positive and negative controls were included in each PCR run. The two positive controls consisted of 1 ng and 0.1 pg of L. donovani (MHOM/NP/03/BPK206/0) DNA, while DNA-free Milli-Q Plus PF water (Millipore, Bedford, MA, USA) was included as the negative control. In addition, DNA extracted from a Leishmania-infected sand fly was also included in each run of PCR as another positive control. In order to confirm that the amplified DNA corresponded well to Leishmania, amplicons were sequenced (3730 DNA Analyzer, Applied Biosystems, Foster City, CA, USA) using the forward and reverse primer. The results were compared with Leishmania sequences from GenBank.
2.5. Statistical methods 2.3. Entomological procedures The identification of houses for sand fly collection was performed in two steps. In the first step, 25 households were randomly selected from each of the six wards, each household in a ward having previously been mapped and
Two methods were used for computing the prevalence of parasite infection in pools of unequal size: the simulation method14 using R (http://cran.r-project.org) and the Farrington method15 using Stata 10 (Stata Corp., College Station, TX, USA). The simulation method uses
Natural infection of Phlebotomus argentipes with Leishmania
Figure 1
1089
Location of the study area in the Sunsari district, Nepal. BPKIHS: B.P. Koirala Institute of Health Sciences.
repeated, randomly generated samples of sand flies with specific prevalence. Each time the prevalence results in the observed number of positive pools, it is stored in the list. The list represents the distribution of possible prevalence. Once the size of the list is sufficient, it can be used to calculate the required quantiles for summarizing the distribution, resulting in confidence intervals. By contrast, the Farrington method uses generalized linear modelling, with a binomial family and a complementary log-log link to calculate the maximum-likelihood estimates of prevalence and confidence limit, when multiple different pool sizes are used. In addition to providing prevalence estimates and con-
fidence intervals, the approach can be used to regress the prevalence on covariates. Comparing the simulations with the results of the generalized linear model indicated that in some instances (i.e. when the sample sizes or pool sizes are small), the result can be different when using two methods. For the sand fly data, we checked whether the two methods provided different results and, if so, reported the difference. If the results were similar, we reported the results of the generalized linear model. The infection rate was calculated by the method of pooled prevalence for variable pool size and perfect tests (assuming 100% sensitivity and specificity).
1090 Table 1
N.R. Bhattarai et al. Origin and distribution of sand fly pools
Wards
Amahibelha Aurabani Bhokraha Dharan-17b Duhabi Tanmuna Total a b
Indoor household collection
Cattle shed collection
No. of pools collected
No. of pools collected
No. of PCR-positive pools
No. of PCR-positive pools
21 9 10 12 49 18
0 1+1a = 2 0 0 1 2+1a = 3
6 1 1 1 5 1
0 0 0 0 1 0
119
4+2a = 6
15
1
Non-Leishmania type, as revealed by sequencing. One pool was PCR negative for the sand fly cytochrome b gene and was excluded from the table.
3. Results
4. Discussion
A total of 135 pools were prepared, each containing 1—20 insects (in total 1084 insects): 120 pools were from indoor household collections and 15 pools were from cattle sheds. All but one pool were found to be PCR positive for the cytochrome b gene, indicating the good quality of DNA in these samples. Seven of these pools were found to be positive by the PCR assay targeting the rRNA genes of Leishmania. Sequencing of the corresponding amplicons showed, in five of the seven pools, the rDNA signature encountered among all Leishmania species, including L. donovani, the main species circulating in the Indian subcontinent. However, the two other pools revealed a slightly different sequence, with a signature compatible with Endotrypanum spp., Leptomonas costaricensis, Sauroleishmania tarentolae or trypanosomatids isolated from immunodepressed patients from Martinique. For simplicity, the parasites encountered in the latter two pools are further referred to as non-Leishmania. The five Leishmania-positive pools were distributed as follows (Table 1): two from Duhabi, one of them from a cattle-shed, and three from Aurabani and Tanmuna, all originating from indoor household collection. Both nonLeishmania infected pools were collected inside households in the same wards as Leishmania-positive pools, that is, Aurabani and Tanmuna. The infection rate was computed by two methods. Using the simulation method, we estimated a rate of 0.578% (95% CI 0.218—1.111) for Leishmania and 0.279% (95% CI 0.060—0.685) for non-Leishmania infection. With the Farrington method, we estimated 0.468% (95% CI 0.195—1.122) for Leishmania and 0.185% (95% CI 0.0463—0.733) for non-Leishmania infection. Since the Farrington method can be used only with sufficient positive pools of adequate size, the ward-wise estimation of Leishmania and non-Leishmania infection rates was only made by the simulation method. Results were distributed as follows for Leishmania: Aurabani: 5.727% (95% CI 0.766—15.047); Tanmuna: 2.711% (95% CI 0.609—6.214) and Duhabi: 0.505% (95% CI 0.108—1.155). With respect to non-Leishmania infections, we found the following: Aurabani: 5.701% (95% CI 0.727—15.26) and Tanmuna: 1.681% (95% CI 0.200—4.480).
We showed the presence of Leishmania as well as other trypanosomatids in the P. argentipes specimens collected in the study area. Depending on the method used, we estimated an infection rate of 0.468—0.578% for Leishmania spp. and 0.185—0.279% for non-Leishmania spp. over the whole study area. Of note, these estimations apply to samples captured in households of wards selected by the KALANET project as having the highest transmission in the past 3 years. Accordingly, they do not necessarily represent the infection rate in the whole endemic region. Nonetheless, our estimation of Leishmania infection rates over the whole area is close to values reported in the neighbouring Indian state of Bihar (0.1%, as estimated by dissection)16 and in Spain (0.027—0.45%, as estimated by PCR-ELISA),5 but different from those reported in Ecuador (3.3%),17 Greece (6.4%)18 and another district of Nepal (6.7%).3 Comparison between studies should be made with extreme care, as transmission features may differ and sampling and experimental protocols are not standardized among these studies. For instance, in the study performed by Pandey et al. in Nepal,3 a smaller sample size was considered (401 insects), individual insects were used instead of pools, samples were collected from five villages instead of six villages, a different and possibly more sensitive PCR assay targeting kDNA was applied, and no statistical methods were considered. Furthermore, a sampling bias could not be excluded in that report. For example, if sampling had been concentrated in a few houses characterized by intensive transmission, that is, many sand flies feeding on the same infected host. This is supported in the present study by estimating infection rates at ward level; in some wards, like Duhabi, a 0.505% infection rate was estimated, while in others, like Aurabani, a rate of 5.727% was estimated. In addition, the authors are likely to have overestimated the infection rate by counting positive amplifications in which the identity of Leishmania was not confirmed. The present study showed that this could be a problem, as non-Leishmania infections were also observed in P. argentipes, sometimes in the same wards (Aurabani and Tanmuna). We could not further elucidate the identity of these other parasites. They were possibly Leptomonas spp.,
Natural infection of Phlebotomus argentipes with Leishmania Endotrypanum spp. or Sauroleishmania spp. (the two latter species have never been reported, to our knowledge, in the Indian subcontinent), or even a parasite similar to the trypanosomatid isolated from immunodepressed patients in Martinique and reported to branch at the base of the Leishmania cluster.19 Sand flies are well known to harbour other parasites than Leishmania: monogenic, like Crithidia species19 or digenic like Trypanosoma leonidasnei,20 flagellates generally not pathogenic for humans, except in rare cases of co-infection. Other studies performed by our group support this idea; despite an extensive survey in the region, we have not encountered this non-Leishmania type in asymptomatic humans21 or VL patients,8 and not in domestic animals either (N.R. Bhattarai, personal communication). With respect to sand fly infection rates with these non-Leishmania parasites, our estimates are lower than those reported from other epidemiological settings: 7.1% by Crithidia species in Panama22 and up to 42% by Trypanosoma leonidasnei in Belize.20 However, our PCR assay does not amplify all flagellates (e.g. T. brucei, T. cruzi8 or T. evansi; J.C. Dujardin, personal communication), hence the prevalence of non-Leishmania infections in sand flies could be underestimated. Further work should be done to identify the parasites isolated from our sand fly sample, but nonetheless our results highlight the need to complement natural infection rate studies with precise typing. The detection of Leishmania is highly relevant for the surveillance of VL and to support control activities. However, particular attention should also be given to non-Leishmania spp., as their precise identification might give indirect information on the behaviour of P. argentipes, the biology of which is still not perfectly understood. Authors’ note: This paper is dedicated to the memory of our colleague and friend, Clive Davies, who passed away in March 2009. Authors’ contributions: NRB, MLD, SR, GvdA, AP, BK, LR, NS, DB and MB contributed to the study design; CRD and MC designed the entomological aspects of the study; J-CD designed the molecular aspects of the study and developed the methods of analysis; MB supervised and coordinated the study; AP supervised and ensured quality control of the field work; SR selected and coordinated the field work; MLD and BK participated in the field work; MLD and LR collected and identified sand flies; NRB prepared the pools of sand files, extracted DNA, ran the PCR and analysed the data; NS and DB participated in the statistical analysis of the sand fly pools; GvdA was responsible for database management; All authors contributed to the preparation of the manuscript and J-CD wrote the final version. All authors read and approved the final manuscript. J-CD is guarantor of the paper. Acknowledgements: We would like to thank Dr Jan Vot´ ypka for his help in providing the DNA extraction protocol and infected sand fly for testing and validating the DNA extraction and control PCR techniques. In addition, our thanks go to all the field workers who helped to collect and process the sand flies in Nepal.
1091 Funding: EU-funded KALANET project (contract no. INCOCT 2005—01537). Conflicts of interest: None declared. Ethical approval: Ethical clearance to conduct the KALANET project was obtained from the ethical committee of the B.P. Koirala Institute of Health Sciences, Dharan, Nepal and the corresponding bodies at the Institute of Tropical Medicine, Antwerp, Belgium and the London School of Hygiene and Tropical Medicine, London, UK.
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