↓ Skip to main content

Flow Cytometry Sorting to Separate Viable Giant Viruses from Amoeba Co-culture Supernatants

Overview of attention for article published in Frontiers in Cellular and Infection Microbiology, January 2017
Altmetric Badge

About this Attention Score

  • Good Attention Score compared to outputs of the same age (72nd percentile)
  • High Attention Score compared to outputs of the same age and source (82nd percentile)

Mentioned by

twitter
4 X users
patent
1 patent

Citations

dimensions_citation
23 Dimensions

Readers on

mendeley
69 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Flow Cytometry Sorting to Separate Viable Giant Viruses from Amoeba Co-culture Supernatants
Published in
Frontiers in Cellular and Infection Microbiology, January 2017
DOI 10.3389/fcimb.2016.00202
Pubmed ID
Authors

Jacques Y. B. Khalil, Thierry Langlois, Julien Andreani, Jean-Marc Sorraing, Didier Raoult, Laurence Camoin, Bernard La Scola

Abstract

Flow cytometry has contributed to virology but has faced many drawbacks concerning detection limits, due to the small size of viral particles. Nonetheless, giant viruses changed many concepts in the world of viruses, as a result of their size and hence opened up the possibility of using flow cytometry to study them. Recently, we developed a high throughput isolation of viruses using flow cytometry and protozoa co-culture. Consequently, isolating a viral mixture in the same sample became more common. Nevertheless, when one virus multiplies faster than others in the mixture, it is impossible to obtain a pure culture of the minority population. Here, we describe a robust sorting system, which can separate viable giant virus mixtures from supernatants. We tested three flow cytometry sorters by sorting artificial mixtures. Purity control was assessed by electron microscopy and molecular biology. As proof of concept, we applied the sorting system to a co-culture supernatant taken from a sample containing a viral mixture that we couldn't separate using end point dilution. In addition to isolating the quick-growing Mimivirus, we sorted and re-cultured a new, slow-growing virus, which we named "Cedratvirus." The sorting assay presented in this paper is a powerful and versatile tool for separating viral populations from amoeba co-cultures and adding value to the new field of flow virometry.

X Demographics

X Demographics

The data shown below were collected from the profiles of 4 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 69 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 1%
Unknown 68 99%

Demographic breakdown

Readers by professional status Count As %
Researcher 13 19%
Student > Ph. D. Student 11 16%
Student > Master 10 14%
Student > Bachelor 7 10%
Professor 3 4%
Other 6 9%
Unknown 19 28%
Readers by discipline Count As %
Agricultural and Biological Sciences 20 29%
Biochemistry, Genetics and Molecular Biology 10 14%
Engineering 5 7%
Immunology and Microbiology 5 7%
Medicine and Dentistry 2 3%
Other 7 10%
Unknown 20 29%
Attention Score in Context

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 September 2022.
All research outputs
#6,350,384
of 23,435,471 outputs
Outputs from Frontiers in Cellular and Infection Microbiology
#1,208
of 6,780 outputs
Outputs of similar age
#116,987
of 423,029 outputs
Outputs of similar age from Frontiers in Cellular and Infection Microbiology
#15
of 93 outputs
Altmetric has tracked 23,435,471 research outputs across all sources so far. This one has received more attention than most of these and is in the 72nd percentile.
So far Altmetric has tracked 6,780 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.6. This one has done well, scoring higher than 81% 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 423,029 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 72% of its contemporaries.
We're also able to compare this research output to 93 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 82% of its contemporaries.