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

Author:

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

Abstract

Abstract 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.

Funder

Wellcome Trust

H2020 European Institute of Innovation and Technology

Coalition for Operational Research on Neglected Tropical Diseases

Publisher

Springer Science and Business Media LLC

Subject

Infectious Diseases,Parasitology

Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3