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BMC Biol. 2018 Mar 29;16(1):36. doi: 10.1186/s12915-018-0496-5.

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

Author information

1
Andalusian Center for Developmental Biology, Consejo Superior de Investigaciones Científicas/Junta de Andalucía/Universidad Pablo de Olavide, Seville, Spain.
2
Department of Molecular Biology and Biochemical Engineering, Universidad Pablo de Olavide, Seville, Spain.
3
GE Healthcare Life Sciences, Maynard Centre, Forest Farm, Whitchurch, Cardiff, UK.
4
Present address: Target Discovery Institute, Nuffield Department of Medicine, University of Oxford, Oxford, UK.
5
Present address: Cell and Developmental Biology Area, Centro Nacional de Investigaciones Cardiovasculares Carlos III (CNIC), Madrid, Spain.
6
Present address: Department of Genetics, University of Seville, Seville, Spain.
7
Centre for Biological Signalling Studies (BIOSS), Laboratory for Bioinformatics and Molecular Genetics, Faculty of Biology, and ZBMZ Center for Biochemistry and Molecular Cell Biology (Faculty of Medicine), Albert-Ludwigs-University of Freiburg, Freiburg, Germany.
8
Andalusian Center for Developmental Biology, Consejo Superior de Investigaciones Científicas/Junta de Andalucía/Universidad Pablo de Olavide, Seville, Spain. martsan@upo.es.
9
Department of Molecular Biology and Biochemical Engineering, Universidad Pablo de Olavide, Seville, Spain. martsan@upo.es.

Abstract

BACKGROUND:

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.

RESULTS:

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 UPRmt and growth.

CONCLUSIONS:

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.

KEYWORDS:

C. elegans; Essential genes; High-content; High-throughput; Image analysis; Mitochondria; Prohibitins; Screens; UPRmt; Worm sorting

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