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The transcriptome of the mosquito Aedes fluviatilis (Diptera: Culicidae), and transcriptional changes associated with its native Wolbachia infection

Overview of attention for article published in BMC Genomics, January 2017
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Title
The transcriptome of the mosquito Aedes fluviatilis (Diptera: Culicidae), and transcriptional changes associated with its native Wolbachia infection
Published in
BMC Genomics, January 2017
DOI 10.1186/s12864-016-3441-4
Pubmed ID
Authors

E. P. Caragata, F. S. Pais, L. A. Baton, J. B. L. Silva, M. H. F. Sorgine, L. A. Moreira

Abstract

Wolbachia is a bacterial endosymbiont that naturally infects a wide range of insect species, and causes drastic changes to host biology. Stable infections of Wolbachia in mosquitoes can inhibit infection with medically important pathogens such as dengue virus and malaria-causing Plasmodium parasites. However, some native Wolbachia strains can enhance infection with certain pathogens, as is the case for the mosquito Aedes fluviatilis, where infection with Plasmodium gallinaceum is enhanced by the native wFlu Wolbachia strain. To better understand the biological interactions between mosquitoes and native Wolbachia infections, and to investigate the process of pathogen enhancement, we used RNA-Seq to generate the transcriptome of Ae. fluviatilis with and without Wolbachia infection. In total, we generated 22,280,160 Illumina paired-end reads from Wolbachia-infected and uninfected mosquitoes, and used these to make a de novo transcriptome assembly, resulting in 58,013 contigs with a median sequence length of 443 bp and an N50 of 2454 bp. Contigs were annotated through local alignments using BlastX, and associated with both gene ontology and KEGG orthology terms. Through baySeq, we identified 159 contigs that were significantly upregulated due to Wolbachia infection, and 98 that were downregulated. Critically, we saw no changes to Toll or IMD immune gene transcription, but did see evidence that wFlu infection altered the expression of several bacterial recognition genes, and immune-related genes that could influence Plasmodium infection. wFlu infection also had a widespread effect on a number of host physiological processes including protein, carbohydrate and lipid metabolism, and oxidative stress. We then compared our data set with transcriptomic data for other Wolbachia infections in Aedes aegypti, and identified a core set of 15 gene groups associated with Wolbachia infection in mosquitoes. While the scale of transcriptional changes associated with wFlu infection might be small, the scope is rather large, which confirms that native Wolbachia infections maintain intricate molecular relationships with their mosquito hosts even after lengthy periods of co-evolution. We have also identified several potential means through which wFlu infection might influence Plasmodium infection in Ae. fluviatilis, and these genes should form the basis of future investigation into the enhancement of Plasmodium by Wolbachia.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 119 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Spain 1 <1%
Unknown 118 99%

Demographic breakdown

Readers by professional status Count As %
Researcher 25 21%
Student > Ph. D. Student 19 16%
Student > Master 17 14%
Student > Bachelor 12 10%
Student > Doctoral Student 5 4%
Other 17 14%
Unknown 24 20%
Readers by discipline Count As %
Agricultural and Biological Sciences 41 34%
Biochemistry, Genetics and Molecular Biology 29 24%
Immunology and Microbiology 4 3%
Medicine and Dentistry 4 3%
Environmental Science 4 3%
Other 9 8%
Unknown 28 24%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 09 January 2017.
All research outputs
#14,081,827
of 24,546,092 outputs
Outputs from BMC Genomics
#4,817
of 11,007 outputs
Outputs of similar age
#211,490
of 430,598 outputs
Outputs of similar age from BMC Genomics
#108
of 227 outputs
Altmetric has tracked 24,546,092 research outputs across all sources so far. This one is in the 41st percentile – i.e., 41% of other outputs scored the same or lower than it.
So far Altmetric has tracked 11,007 research outputs from this source. They receive a mean Attention Score of 4.8. This one has gotten more attention than average, scoring higher than 54% 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 430,598 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 50% of its contemporaries.
We're also able to compare this research output to 227 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 50% of its contemporaries.