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Identification of candidate infection genes from the model entomopathogenic nematode Heterorhabditis bacteriophora

Overview of attention for article published in BMC Genomics, January 2017
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  • Good Attention Score compared to outputs of the same age (67th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (64th percentile)

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Title
Identification of candidate infection genes from the model entomopathogenic nematode Heterorhabditis bacteriophora
Published in
BMC Genomics, January 2017
DOI 10.1186/s12864-016-3468-6
Pubmed ID
Authors

Jonathan Vadnal, Ramesh Ratnappan, Melissa Keaney, Eric Kenney, Ioannis Eleftherianos, Damien O’Halloran, John M. Hawdon

Abstract

Despite important progress in the field of innate immunity, our understanding of host immune responses to parasitic nematode infections lags behind that of responses to microbes. A limiting factor has been the obligate requirement for a vertebrate host which has hindered investigation of the parasitic nematode infective process. The nematode parasite Heterorhabditis bacteriophora offers great potential as a model to genetically dissect the process of infection. With its mutualistic Photorhabdus luminescens bacteria, H. bacteriophora invades multiple species of insects, which it kills and exploits as a food source for the development of several nematode generations. The ability to culture the life cycle of H. bacteriophora on plates growing the bacterial symbiont makes it a very exciting model of parasitic infection that can be used to unlock the molecular events occurring during infection of a host that are inaccessible using vertebrate hosts. To profile the transcriptional response of an infective nematode during the early stage of infection, we performed next generation RNA sequencing on H. bacteriophora IJs incubated in Manduca sexta hemolymph plasma for 9 h. A subset of up-regulated and down-regulated genes were validated using qRT-PCR. Comparative analysis of the transcriptome with untreated controls found a number of differentially expressed genes (DEGs) which cover a number of different functional categories. A subset of DEGs is conserved across Clade V parasitic nematodes revealing an array of candidate parasitic genes. Our analysis reveals transcriptional changes in the regulation of a large number of genes, most of which have not been shown previously to play a role in the process of infection. A significant proportion of these genes are unique to parasitic nematodes, suggesting the identification of a group of parasitism factors within nematodes. Future studies using these candidates may provide functional insight into the process of nematode parasitism and also the molecular evolution of parasitism within nematodes.

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The data shown below were collected from the profiles of 6 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 37 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 37 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 6 16%
Student > Bachelor 6 16%
Researcher 5 14%
Student > Master 4 11%
Professor > Associate Professor 3 8%
Other 5 14%
Unknown 8 22%
Readers by discipline Count As %
Agricultural and Biological Sciences 13 35%
Biochemistry, Genetics and Molecular Biology 8 22%
Environmental Science 2 5%
Immunology and Microbiology 2 5%
Social Sciences 1 3%
Other 1 3%
Unknown 10 27%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 13 September 2017.
All research outputs
#7,193,557
of 22,925,760 outputs
Outputs from BMC Genomics
#3,399
of 10,676 outputs
Outputs of similar age
#134,899
of 421,214 outputs
Outputs of similar age from BMC Genomics
#80
of 228 outputs
Altmetric has tracked 22,925,760 research outputs across all sources so far. This one has received more attention than most of these and is in the 68th percentile.
So far Altmetric has tracked 10,676 research outputs from this source. They receive a mean Attention Score of 4.7. This one has gotten more attention than average, scoring higher than 67% 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 421,214 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 67% of its contemporaries.
We're also able to compare this research output to 228 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 64% of its contemporaries.