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A deep sequencing approach to estimate Plasmodium falciparum complexity of infection (COI) and explore apical membrane antigen 1 diversity

Overview of attention for article published in Malaria Journal, December 2017
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  • Good Attention Score compared to outputs of the same age (70th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (63rd percentile)

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9 tweeters
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1 Facebook page

Citations

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34 Dimensions

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83 Mendeley
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Title
A deep sequencing approach to estimate Plasmodium falciparum complexity of infection (COI) and explore apical membrane antigen 1 diversity
Published in
Malaria Journal, December 2017
DOI 10.1186/s12936-017-2137-9
Pubmed ID
Authors

Robin H. Miller, Nicholas J. Hathaway, Oksana Kharabora, Kashamuka Mwandagalirwa, Antoinette Tshefu, Steven R. Meshnick, Steve M. Taylor, Jonathan J. Juliano, V. Ann Stewart, Jeffrey A. Bailey

Abstract

Humans living in regions with high falciparum malaria transmission intensity harbour multi-strain infections comprised of several genetically distinct malaria haplotypes. The number of distinct malaria parasite haplotypes identified from an infected human host at a given time is referred to as the complexity of infection (COI). In this study, an amplicon-based deep sequencing method targeting the Plasmodium falciparum apical membrane antigen 1 (pfama1) was utilized to (1) investigate the relationship between P. falciparum prevalence and COI, (2) to explore the population genetic structure of P. falciparum parasites from malaria asymptomatic individuals participating in the 2007 Demographic and Health Survey (DHS) in the Democratic Republic of Congo (DRC), and (3) to explore selection pressures on geospatially divergent parasite populations by comparing AMA1 amino acid frequencies in the DRC and Mali. A total of 900 P. falciparum infections across 11 DRC provinces were examined. Deep sequencing of both individuals, for COI analysis, and pools of individuals, to examine population structure, identified 77 unique pfama1 haplotypes. The majority of individual infections (64.5%) contained polyclonal (COI > 1) malaria infections based on the presence of genetically distinct pfama1 haplotypes. A minimal correlation between COI and malaria prevalence as determined by sensitive real-time PCR was identified. Population genetic analyses revealed extensive haplotype diversity, the vast majority of which was shared across the sites. AMA1 amino acid frequencies were similar between parasite populations in the DRC and Mali. Amplicon-based deep sequencing is a useful tool for the detection of multi-strain infections that can aid in the understanding of antigen heterogeneity of potential malaria vaccine candidates, population genetics of malaria parasites, and factors that influence complex, polyclonal malaria infections. While AMA1 and other diverse markers under balancing selection may perform well for understanding COI, they may offer little geographic or temporal discrimination between parasite populations.

Twitter Demographics

The data shown below were collected from the profiles of 9 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 83 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 83 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 17 20%
Researcher 14 17%
Student > Master 12 14%
Student > Bachelor 7 8%
Student > Postgraduate 5 6%
Other 13 16%
Unknown 15 18%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 23 28%
Agricultural and Biological Sciences 12 14%
Immunology and Microbiology 7 8%
Engineering 6 7%
Computer Science 4 5%
Other 10 12%
Unknown 21 25%

Attention Score in Context

This research output has an Altmetric Attention Score of 5. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 30 June 2018.
All research outputs
#4,210,799
of 16,026,607 outputs
Outputs from Malaria Journal
#1,243
of 4,518 outputs
Outputs of similar age
#118,962
of 410,532 outputs
Outputs of similar age from Malaria Journal
#173
of 492 outputs
Altmetric has tracked 16,026,607 research outputs across all sources so far. This one has received more attention than most of these and is in the 73rd percentile.
So far Altmetric has tracked 4,518 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.0. This one has gotten more attention than average, scoring higher than 72% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 410,532 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 70% of its contemporaries.
We're also able to compare this research output to 492 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 63% of its contemporaries.