Development and pilot application of a point-of-need molecular xenomonitoring protocol for tsetse (Glossina sp.) in a low-resource setting
Saldanha, I.; Aziku, E.; Trima, A. T.; Drapari, V.; Garrod, G.; Ombanya, H.; Tirados, I.; Betson, M.; Mugenyi, A.; Dunkley, S.; Torr, S. J.; Hope, A.; Cunningham, L. J.
Show abstract
BackgroundTsetse flies (Glossina sp.) are the primary vectors of trypanosomes causing human African trypanosomiasis (HAT) and animal African trypanosomiasis (AAT). Disease surveillance can be carried out by detecting Trypanosoma DNA in tsetse, also known as molecular xenomonitoring. Whilst molecular methods can increase the efficiency and sensitivity of pathogen detection, trained staff and a well-equipped laboratory are required. In many cases, DNA extraction and screening is outsourced to a central laboratory in a major city either in-country or abroad, far removed from original tsetse collection sites. This increases results turnaround time, incurs transportation costs, and can lead to sample loss or damage. Methodology/Principle FindingsWe set out to develop, optimise and trial methods for tsetse xenomonitoring in a low-resource point-of-need setting. A low-cost protocol was developed consisting of rapid alkali-based DNA extraction and Trypanosoma detection qPCR assays using air-dryable reagent mixes. A minimally-equipped laboratory was established in a field station in Arua, Uganda. Following a training workshop, three entomology technicians carried out screening on 286 tsetse collected over a nine-week study period. The technicians consistently extracted high quality DNA (98% success rate) and were able to successfully detect T. brucei sensu lato, T. congolense and T. vivax DNA in 3.6% - 4.3% (95% confidence interval [1.73, 7.73]) of total tsetse. Conclusions/SignificanceThis study demonstrated that sensitive molecular xenomonitoring of HAT and AAT pathogens can be carried out without the need for cold-chain storage or high-powered equipment. Further improvements to the system might be achieved by modifying the DNA extraction protocol to enable high-throughput or pooled samples, increasing the sensitivity of the T. b. gambiense DNA detection assay and exploring more sustainable power sources. Author SummaryTsetse flies spread the parasitic diseases human African trypanosomiasis (sleeping sickness) and animal African trypanosomiasis (nagana) that impact populations across sub-Saharan Africa. Disease surveillance can be carried out using tests to detect parasite DNA in tsetse, termed molecular xenomonitoring. Currently, these methods are too complex, costly and logistically-challenging to be carried out in remote areas where sleeping sickness is a problem. However, advances in molecular testing technology are now making this a possibility. We set out to develop a tsetse molecular xenomonitoring system using a basic laboratory set-up in Arua, Uganda. The protocol comprised a low-cost method to extract DNA from tsetse, a portable qPCR machine to test samples and air-dried reagents that did not require cold storage. Following a two-week training workshop, three technicians went on to carry out testing on 286 tsetse over a nine-week period. The technicians were able to consistently extract high-quality DNA (98% success rate) and successfully detected trypanosome parasite DNA in 30 (10.7%) tsetse samples. Whilst there are still challenges to overcome, this study has demonstrated that molecular xenomonitoring of tsetse can be carried out without the need for trainees with previous molecular experience, refrigerated reagents or high-powered equipment.
Matching journals
The top 1 journal accounts for 50% of the predicted probability mass.
Similar papers in this journal
- Tsetse blood-meal sources, endosymbionts, and trypanosome infections provide insight into African trypanosomiasis transmission in the Maasai Mara National Reserve, a wildlife-human-livestock interface 97%
- Insights into Trypanosomiasis Transmission: Age, Infection Rates and Bloodmeal Analysis of Glossina fuscipes fuscipes in N.W. Uganda 96%
- Targeting a highly repetitive genomic sequence for sensitive and specific molecular detection of the filarial parasite Mansonella perstans from human blood and mosquitoes 96%
Similar papers in this journal
- Evaluation of a pan-Leishmania SL-RNA qPCR assay for parasite detection in laboratory-reared and field-collected sand flies and reservoir hosts. 96%
- Testing a non-destructive assay to track Plasmodium sporozoites in mosquitoes over time 96%
- Triatoma dimidiata, domestic animals and acute Chagas disease: A 10 year follow-up after an eco-bio-social intervention 95%
Similar papers in this journal
- Validation of a novel multiplex real-time PCR assay for Trypanosoma cruzi detection and quantification in acai pulp 96%
- A LAMP assay for the rapid and robust assessment of Wolbachia infection in Aedes aegypti under field and laboratory conditions 94%
- Integrating post-validation surveillance of lymphatic filariasis with the WHO STEPwise approach to non-communicable disease risk factor surveillance in Niue, a study protocol 94%
Similar papers in this journal
- Investigation of the global transportation of Culicoides biting midges, vectors of livestock and equid arboviruses, from flower-packing plants in Kenya 94%
- Lack of robust evidence for a Wolbachia infection in Anopheles gambiae from Burkina Faso 93%
- Preimaginal development of Aedes aegypti in brackish water produces adult mosquitoes with thicker cuticles and greater insecticide resistance 93%
Similar papers in this journal
- Widespread occurrence of benzimidazole resistance single nucleotide polymorphisms in the canine hookworm, Ancylostoma caninum, in Australia 93%
- High Plasmodium infection intensity in naturally infected malaria vectors in Africa 93%
- High prevalence of Plasmodium malariae and Plasmodium ovale in co-infections with Plasmodium falciparum in asymptomatic malaria parasite carriers in Southwest Nigeria 93%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.