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Applied genomics: data mining reveals species-specific malaria diagnostic targets more sensitive than 18S rRNA.

ABSTRACT: Accurate and rapid diagnosis of malaria infections is crucial for implementing species-appropriate treatment and saving lives. Molecular diagnostic tools are the most accurate and sensitive method of detecting Plasmodium, differentiating between Plasmodium species, and detecting subclinical infections. Despite available whole-genome sequence data for Plasmodium falciparum and P. vivax, the majority of PCR-based methods still rely on the 18S rRNA gene targets. Historically, this gene has served as the best target for diagnostic assays. However, it is limited in its ability to detect mixed infections in multiplex assay platforms without the use of nested PCR. New diagnostic targets are needed. Ideal targets will be species specific, highly sensitive, and amenable to both single-step and multiplex PCRs. We have mined the genomes of P. falciparum and P. vivax to identify species-specific, repetitive sequences that serve as new PCR targets for the detection of malaria. We show that these targets (Pvr47 and Pfr364) exist in 14 to 41 copies and are more sensitive than 18S rRNA when utilized in a single-step PCR. Parasites are routinely detected at levels of 1 to 10 parasites/?l. The reaction can be multiplexed to detect both species in a single reaction. We have examined 7 P. falciparum strains and 91 P. falciparum clinical isolates from Tanzania and 10 P. vivax strains and 96 P. vivax clinical isolates from Venezuela, and we have verified a sensitivity and specificity of ?100% for both targets compared with a nested 18S rRNA approach. We show that bioinformatics approaches can be successfully applied to identify novel diagnostic targets and improve molecular methods for pathogen detection. These novel targets provide a powerful alternative molecular diagnostic method for the detection of P. falciparum and P. vivax in conventional or multiplex PCR platforms.

SUBMITTER: Demas A

PROVIDER: S-EPMC3147814 | biostudies-other | 2011 Jul

REPOSITORIES: biostudies-other

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Applied genomics: data mining reveals species-specific malaria diagnostic targets more sensitive than 18S rRNA.

Demas Allison A Oberstaller Jenna J DeBarry Jeremy J Lucchi Naomi W NW Srinivasamoorthy Ganesh G Sumari Deborah D Kabanywanyi Abdunoor M AM Villegas Leopoldo L Escalante Ananias A AA Kachur S Patrick SP Barnwell John W JW Peterson David S DS Udhayakumar Venkatachalam V Kissinger Jessica C JC

Journal of clinical microbiology 20110427 7

Accurate and rapid diagnosis of malaria infections is crucial for implementing species-appropriate treatment and saving lives. Molecular diagnostic tools are the most accurate and sensitive method of detecting Plasmodium, differentiating between Plasmodium species, and detecting subclinical infections. Despite available whole-genome sequence data for Plasmodium falciparum and P. vivax, the majority of PCR-based methods still rely on the 18S rRNA gene targets. Historically, this gene has served a ...[more]

PMID: 21525225

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Project description:BackgroundA new more highly sensitive rapid diagnostic test (HS-RDT) for Plasmodium falciparum malaria (Alere™/Abbott Malaria Ag P.f RDT [05FK140], now called NxTek™ Eliminate Malaria Ag Pf) was launched in 2017. The test has already been used in many research studies in a wide range of geographies and use cases.MethodsIn this study, we collate all published and available unpublished studies that use the HS-RDT and assess its performance in (i) prevalence surveys, (ii) clinical diagnosis, (iii) screening pregnant women, and (iv) active case detection. Two individual-level data sets from asymptomatic populations are used to fit logistic regression models to estimate the probability of HS-RDT positivity based on histidine-rich protein 2 (HRP2) concentration and parasite density. The performance of the HS-RDT in prevalence surveys is estimated by calculating the sensitivity and positive proportion in comparison to polymerase chain reaction (PCR) and conventional malaria RDTs.ResultsWe find that across 18 studies, in prevalence surveys, the mean sensitivity of the HS-RDT is estimated to be 56.1% (95% confidence interval [CI] 46.9-65.4%) compared to 44.3% (95% CI 32.6-56.0%) for a conventional RDT (co-RDT) when using nucleic acid amplification techniques as the reference standard. In studies where prevalence was estimated using both the HS-RDT and a co-RDT, we found that prevalence was on average 46% higher using a HS-RDT compared to a co-RDT. For use in clinical diagnosis and screening pregnant women, the HS-RDT was not significantly more sensitive than a co-RDT.ConclusionsOverall, the evidence presented here suggests that the HS-RDT is more sensitive in asymptomatic populations and could provide a marginal improvement in clinical diagnosis and screening pregnant women. Although the HS-RDT has limited temperature stability and shelf-life claims compared to co-RDTs, there is no evidence to suggest, given this test has the same cost as current RDTs, it would have any negative impacts in terms of malaria misdiagnosis if it were widely used in all four population groups explored here.

Project description:For photosynthetic microbial eukaryotes, the rate-limiting step in NO3- assimilation is its reduction to nitrite (NO2-), which is catalyzed by assimilatory nitrate reductase (NR). Oceanic productivity is primarily limited by available nitrogen and, although nitrate is the most abundant form of available nitrogen in oceanic waters, little is known about the identity of microbial eukaryotes that take up nitrate. This lack of knowledge is especially severe for ice-covered seas that are being profoundly affected by climate change. To address this, we examined the distribution and diversity of NR genes in the Arctic region by way of clone libraries and data mining of available metagenomes (total of 4.24 billion reads). We directly compared NR clone phylogenies with the V4 region of the 18S rRNA gene (DNA pool) and 18S rRNA (RNA pool) at two ice-influenced stations in the Canada Basin (Beaufort Sea). The communities from the two nucleic acid templates were similar at the level of major groups, and species identified by way of NR gene phylogeny and microscopy were a subset of the 18S results. Most NR genes from arctic clone libraries matched diatoms and chromist nanoflagellates, including novel clades, while the NR genes in arctic eukaryote metagenomes were dominated by chlorophyte NR, in keeping with the ubiquitous occurrence of Mamiellophyceae in the Arctic Ocean. Overall, these data suggest that a dynamic and mixed eukaryotic community utilizes nitrate across the Arctic region, and they show the potential utility of NR as a tool to identify ongoing changes in arctic photosynthetic communities.IMPORTANCE To better understand the diversity of primary producers in the Arctic Ocean, we targeted a nitrogen cycle gene, NR, which is required for phytoplankton to assimilate nitrate into organic forms of nitrogen macromolecules. We compared this to the more detailed taxonomy from ice-influenced stations using a general taxonomic gene (18S rRNA). NR genes were ubiquitous and could be classified as belonging to diatoms, dinoflagellates, other flagellates, chlorophytes, and unknown microbial eukaryotes, suggesting novel diversity of both species and metabolism in arctic phytoplankton.

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Applied genomics: data mining reveals species-specific malaria diagnostic targets more sensitive than 18S rRNA.

Publications

Applied genomics: data mining reveals species-specific malaria diagnostic targets more sensitive than 18S rRNA.

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