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Combined flow cytometry and high-throughput image analysis for the study of essential genes in Caenorhabditis elegans

Overview of attention for article published in BMC Biology, March 2018
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (86th percentile)

Mentioned by

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31 tweeters

Citations

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7 Dimensions

Readers on

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29 Mendeley
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Title
Combined flow cytometry and high-throughput image analysis for the study of essential genes in Caenorhabditis elegans
Published in
BMC Biology, March 2018
DOI 10.1186/s12915-018-0496-5
Pubmed ID
Authors

Blanca Hernando-Rodríguez, Annmary Paul Erinjeri, María Jesús Rodríguez-Palero, Val Millar, Sara González-Hernández, María Olmedo, Bettina Schulze, Ralf Baumeister, Manuel J. Muñoz, Peter Askjaer, Marta Artal-Sanz

Abstract

Advances in automated image-based microscopy platforms coupled with high-throughput liquid workflows have facilitated the design of large-scale screens utilising multicellular model organisms such as Caenorhabditis elegans to identify genetic interactions, therapeutic drugs or disease modifiers. However, the analysis of essential genes has lagged behind because lethal or sterile mutations pose a bottleneck for high-throughput approaches, and a systematic way to analyse genetic interactions of essential genes in multicellular organisms has been lacking. In C. elegans, non-conditional lethal mutations can be maintained in heterozygosity using chromosome balancers, commonly expressing green fluorescent protein (GFP) in the pharynx. However, gene expression or function is typically monitored by the use of fluorescent reporters marked with the same fluorophore, presenting a challenge to sort worm populations of interest, particularly at early larval stages. Here, we develop a sorting strategy capable of selecting homozygous mutants carrying a GFP stress reporter from GFP-balanced animals at the second larval stage. Because sorting is not completely error-free, we develop an automated high-throughput image analysis protocol that identifies and discards animals carrying the chromosome balancer. We demonstrate the experimental usefulness of combining sorting of homozygous lethal mutants and automated image analysis in a functional genomic RNA interference (RNAi) screen for genes that genetically interact with mitochondrial prohibitin (PHB). Lack of PHB results in embryonic lethality, while homozygous PHB deletion mutants develop into sterile adults due to maternal contribution and strongly induce the mitochondrial unfolded protein response (UPRmt). In a chromosome-wide RNAi screen for C. elegans genes having human orthologues, we uncover both known and new PHB genetic interactors affecting the UPRmtand growth. The method presented here allows the study of balanced lethal mutations in a high-throughput manner. It can be easily adapted depending on the user's requirements and should serve as a useful resource for the C. elegans community for probing new biological aspects of essential nematode genes as well as the generation of more comprehensive genetic networks.

Twitter Demographics

The data shown below were collected from the profiles of 31 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 29 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 29 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 4 14%
Researcher 4 14%
Student > Bachelor 4 14%
Other 3 10%
Student > Master 3 10%
Other 6 21%
Unknown 5 17%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 9 31%
Agricultural and Biological Sciences 6 21%
Social Sciences 2 7%
Environmental Science 1 3%
Nursing and Health Professions 1 3%
Other 4 14%
Unknown 6 21%

Attention Score in Context

This research output has an Altmetric Attention Score of 16. 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 28 June 2019.
All research outputs
#1,285,206
of 15,922,732 outputs
Outputs from BMC Biology
#412
of 1,363 outputs
Outputs of similar age
#38,454
of 280,957 outputs
Outputs of similar age from BMC Biology
#1
of 2 outputs
Altmetric has tracked 15,922,732 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 91st percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,363 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 19.6. This one has gotten more attention than average, scoring higher than 69% 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 280,957 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 86% of its contemporaries.
We're also able to compare this research output to 2 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them