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Meta-Analysis of Aedes aegypti Expression Datasets: Comparing Virus Infection and Blood-Fed Transcriptomes to Identify Markers of Virus Presence

Overview of attention for article published in Frontiers in Bioengineering and Biotechnology, January 2018
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Title
Meta-Analysis of Aedes aegypti Expression Datasets: Comparing Virus Infection and Blood-Fed Transcriptomes to Identify Markers of Virus Presence
Published in
Frontiers in Bioengineering and Biotechnology, January 2018
DOI 10.3389/fbioe.2017.00084
Pubmed ID
Authors

Kiyoshi Ferreira Fukutani, José Irahe Kasprzykowski, Alexandre Rossi Paschoal, Matheus de Souza Gomes, Aldina Barral, Camila I. de Oliveira, Pablo Ivan Pereira Ramos, Artur Trancoso Lopo de Queiroz

Abstract

The mosquito Aedes aegypti (L.) is vector of several arboviruses including dengue, yellow fever, chikungunya, and more recently zika. Previous transcriptomic studies have been performed to elucidate altered pathways in response to viral infection. However, the intrinsic coupling between alimentation and infection were unappreciated in these studies. Feeding is required for the initial mosquito contact with the virus and these events are highly dependent. Addressing this relationship, we reinterrogated datasets of virus-infected mosquitoes with two different diet schemes (fed and unfed mosquitoes), evaluating the metabolic cross-talk during both processes. We constructed coexpression networks with the differentially expressed genes of these comparison: virus-infected versus blood-fed mosquitoes and virus-infected versus unfed mosquitoes. Our analysis identified one module with 110 genes that correlated with infection status (representing ~0.7% of the A. aegypti genome). Furthermore, we performed a machine-learning approach and summarized the infection status using only four genes (AAEL012128, AAEL014210, AAEL002477, and AAEL005350). While three of the four genes were annotated as hypothetical proteins, AAEL012128 gene is a membrane amino acid transporter correlated with viral envelope binding. This gene alone is able to discriminate all infected samples and thus should have a key role to discriminate viral infection in the A. aegypti mosquito. Moreover, validation using external datasets found this gene as differentially expressed in four transcriptomic experiments. Therefore, these genes may serve as a proxy of viral infection in the mosquito and the others 106 identified genes provides a framework to future studies.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 63 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 63 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 14 22%
Student > Master 10 16%
Student > Doctoral Student 7 11%
Student > Postgraduate 5 8%
Student > Bachelor 4 6%
Other 11 17%
Unknown 12 19%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 16 25%
Agricultural and Biological Sciences 11 17%
Medicine and Dentistry 7 11%
Nursing and Health Professions 2 3%
Computer Science 2 3%
Other 11 17%
Unknown 14 22%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 January 2018.
All research outputs
#14,963,216
of 23,015,156 outputs
Outputs from Frontiers in Bioengineering and Biotechnology
#2,221
of 6,719 outputs
Outputs of similar age
#256,719
of 443,312 outputs
Outputs of similar age from Frontiers in Bioengineering and Biotechnology
#16
of 33 outputs
Altmetric has tracked 23,015,156 research outputs across all sources so far. This one is in the 32nd percentile – i.e., 32% of other outputs scored the same or lower than it.
So far Altmetric has tracked 6,719 research outputs from this source. They receive a mean Attention Score of 3.4. This one has gotten more attention than average, scoring higher than 61% 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 443,312 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 39th percentile – i.e., 39% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 33 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 51% of its contemporaries.