DjinniChip: evaluation of a novel molecular rapid diagnostic device for the detection of Chlamydia trachomatis in trachoma-endemic areas

27 Oct 2020
Tamsyn R. Derrick, Natalia Sandetskaya, Harry Pickering, Andreas Kölsch, Athumani Ramadhani, Elias Mafuru, Patrick Massae, Aiweda Malisa, Tara Mtuy, Matthew J. Burton, Martin J. Holland & Dirk Kuhlmeier

Background

The clinical signs of active trachoma are often present in the absence of ocular Chlamydia trachomatis infection, particularly following mass drug administration. Treatment decisions following impact surveys and in post-control surveillance for communities are currently based on the prevalence of clinical signs, which may result in further unnecessary distribution of mass antibiotic treatment and the increased spread of macrolide resistance alleles in ‘off-target’ bacterial species. We therefore developed a simple, fast, low cost diagnostic assay (DjinniChip) for diagnosis of ocular C. trachomatis for use by trachoma control programmes.

Methods

The study was conducted in the UK, Germany and Tanzania. For clinical testing in Tanzania, specimens from a sample of 350 children between the ages of 7 to 15 years, which were part of a longitudinal cohort that began in February 2012 were selected. Two ocular swabs were taken from the right eye. The second swab was collected dry, kept cool in the field and archived at – 80 °C before sample lysis for DjinniChip detection and parallel nucleic acid purification and detection/quantification by qPCR assay.

Results

DjinniChip was able to reliably detect > 10 copies of C. trachomatis per test and correctly identified 7/10 Quality Control for Molecular Diagnostics C. trachomatis panel samples, failing to detect 3 positive samples with genome equivalent amounts ≤ 10 copies. DjinniChip performed well across a range of typical trachoma field conditions and when used by lay personnel using a series of mock samples. In the laboratory in Tanzania, using clinical samples the sensitivity and specificity of DjinniChip for C. trachomatis was 66% (95% CI 51–78) and 94.8 (95% CI 91–97%) with an overall accuracy of 90.1 (95% CI 86.4–93).

Conclusions

DjinniChip performance is extremely promising, particularly its ability to detect low concentrations of C. trachomatis and its usability in field conditions. The DjinniChip requires further development to reduce inhibition and advance toward a closed system. DjinniChip results did not vary between local laboratory results and typical trachoma field settings, illustrating its potential for use in low-resource areas to prevent unnecessary rounds of MDA and to monitor for C. trachomatis recrudescence.