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Purification and proteomics of pathogen-modified vacuoles and membranes

Overview of attention for article published in Frontiers in Cellular and Infection Microbiology, June 2015
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Title
Purification and proteomics of pathogen-modified vacuoles and membranes
Published in
Frontiers in Cellular and Infection Microbiology, June 2015
DOI 10.3389/fcimb.2015.00048
Pubmed ID
Authors

Jo-Ana Herweg, Nicole Hansmeier, Andreas Otto, Anna C. Geffken, Prema Subbarayal, Bhupesh K. Prusty, Dörte Becher, Michael Hensel, Ulrich E. Schaible, Thomas Rudel, Hubert Hilbi

Abstract

Certain pathogenic bacteria adopt an intracellular lifestyle and proliferate in eukaryotic host cells. The intracellular niche protects the bacteria from cellular and humoral components of the mammalian immune system, and at the same time, allows the bacteria to gain access to otherwise restricted nutrient sources. Yet, intracellular protection and access to nutrients comes with a price, i.e., the bacteria need to overcome cell-autonomous defense mechanisms, such as the bactericidal endocytic pathway. While a few bacteria rupture the early phagosome and escape into the host cytoplasm, most intracellular pathogens form a distinct, degradation-resistant and replication-permissive membranous compartment. Intracellular bacteria that form unique pathogen vacuoles include Legionella, Mycobacterium, Chlamydia, Simkania, and Salmonella species. In order to understand the formation of these pathogen niches on a global scale and in a comprehensive and quantitative manner, an inventory of compartment-associated host factors is required. To this end, the intact pathogen compartments need to be isolated, purified and biochemically characterized. Here, we review recent progress on the isolation and purification of pathogen-modified vacuoles and membranes, as well as their proteomic characterization by mass spectrometry and different validation approaches. These studies provide the basis for further investigations on the specific mechanisms of pathogen-driven compartment formation.

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The data shown below were collected from the profile of 1 X user 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 102 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
India 1 <1%
Germany 1 <1%
Norway 1 <1%
Unknown 99 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 28 27%
Researcher 20 20%
Student > Master 11 11%
Student > Doctoral Student 9 9%
Student > Bachelor 8 8%
Other 11 11%
Unknown 15 15%
Readers by discipline Count As %
Agricultural and Biological Sciences 39 38%
Biochemistry, Genetics and Molecular Biology 22 22%
Immunology and Microbiology 12 12%
Medicine and Dentistry 7 7%
Engineering 3 3%
Other 3 3%
Unknown 16 16%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 24 May 2018.
All research outputs
#20,274,720
of 22,807,037 outputs
Outputs from Frontiers in Cellular and Infection Microbiology
#5,927
of 6,360 outputs
Outputs of similar age
#223,670
of 267,792 outputs
Outputs of similar age from Frontiers in Cellular and Infection Microbiology
#10
of 12 outputs
Altmetric has tracked 22,807,037 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 6,360 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.3. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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 267,792 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 12 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.