Genome-wide RNAi screen for synthetic lethal interactions with the C. elegans kinesin-5 homolog BMK-1

Uncovering hidden cancer self-dependencies through analysis of shRNA-level dependency scores

Large-scale short hairpin RNA (shRNA) screens on well-characterized human cancer cell lines have been widely used to identify novel cancer dependencies. However, the off-target effects of shRNA reagents pose a significant challenge in the analysis of these screens. To mitigate these off-target effects, various approaches have been proposed that aggregate different shRNA viability scores targeting a gene into a single gene-level viability score. Most computational methods for discovering cancer dependencies rely on these gene-level scores. In this paper, we propose a computational method, named NBDep, to find cancer self-dependencies by directly analyzing shRNA-level dependency scores instead of gene-level scores. The NBDep algorithm begins by removing known batch effects of the shRNAs and selecting a subset of concordant shRNAs for each gene. It then uses negative binomial random effects models to statistically assess the dependency between genetic alterations and the viabilities of cell lines by incorporating all shRNA dependency scores of each gene into the model. We applied NBDep to the shRNA dependency scores available at Project DRIVE, which covers 26 different types of cancer. The proposed method identified more well-known and putative cancer genes compared to alternative gene-level approaches in pan-cancer and cancer-specific analyses. Additionally, we demonstrated that NBDep controls type-I error and outperforms statistical tests based on gene-level scores in simulation studies.

Redundant microtubule crosslinkers prevent meiotic spindle bending to ensure diploid offspring in C. elegans

Oocyte meiotic spindles mediate the expulsion of ¾ of the genome into polar bodies to generate diploid zygotes in nearly all animal species. Failures in this process result in aneuploid or polyploid offspring that are typically inviable. Accurate meiotic chromosome segregation and polar body extrusion require the spindle to elongate while maintaining its structural integrity. Previous studies have implicated three hypothetical activities during this process, including microtubule crosslinking, microtubule sliding and microtubule polymerization. However, how these activities regulate spindle rigidity and elongation as well as the exact proteins involved in the activities remain unclear. We discovered that C. elegans meiotic anaphase spindle integrity is maintained through redundant microtubule crosslinking activities of the Kinesin-5 family motor BMK-1, the microtubule bundling protein SPD-1/PRC1, and the Kinesin-4 family motor, KLP-19. Using time-lapse imaging, we found that single depletion of KLP-19KIF4A, SPD-1PRC1 or BMK-1Eg5 had minimal effects on anaphase B spindle elongation velocity. In contrast, double depletion of SPD-1PRC1 and BMK-1Eg5 or double depletion of KLP-19KIF4A and BMK-1Eg5 resulted in spindles that elongated faster, bent in a myosin-dependent manner, and had a high rate of polar body extrusion errors. Bending spindles frequently extruded both sets of segregating chromosomes into two separate polar bodies. Normal anaphase B velocity was observed after double depletion of KLP-19KIF4A and SPD-1PRC1. These results suggest that KLP-19KIF4A and SPD-1PRC1 act in different pathways, each redundant with a separate BMK-1Eg5 pathway in regulating meiotic spindle elongation. Depletion of ZYG-8, a doublecortin-related microtubule binding protein, led to slower anaphase B spindle elongation. We found that ZYG-8DCLK1 acts by excluding SPD-1PRC1 from the spindle. Thus, three mechanistically distinct microtubule regulation modules, two based on crosslinking, and one based on exclusion of crosslinkers, power the mechanism that drives spindle elongation and structural integrity during anaphase B of C.elegans female meiosis.

Yolk-deprived Caenorhabditis elegans secure brood size at the expense of competitive fitness

Oviparous animals support reproduction via the incorporation of yolk as a nutrient source into the eggs. In Caenorhabditis elegans, however, yolk proteins seem dispensable for fecundity, despite constituting the vast majority of the embryonic protein pool and acting as carriers for nutrient-rich lipids. Here, we used yolk protein-deprived C. elegans mutants to gain insight into the traits that may yet be influenced by yolk rationing. We show that massive yolk provisioning confers a temporal advantage during embryogenesis, while also increasing early juvenile body size and promoting competitive fitness. Opposite to species that reduce egg production under yolk deprivation, our results indicate that C. elegans relies on yolk as a fail-safe to secure offspring survival, rather than to maintain offspring numbers.

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

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 (UPR^mt). In a chromosome-wide RNAi screen for C. elegans genes having human orthologues, we uncover both known and new PHB genetic interactors affecting the UPR^mt 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.

Electronic supplementary material

The online version of this article (10.1186/s12915-018-0496-5) contains supplementary material, which is available to authorized users.

A genome-scale RNAi screen for genetic interactors of the dynein co-factor nud-2 in Caenorhabditis elegans

Cytoplasmic dynein 1 (dynein) is the predominant microtubule minus end-directed motor in animals and participates in a wide range of cellular processes, including membrane trafficking, nuclear migration, and cell division. Dynein's functional diversity depends on co-factors that regulate its subcellular localization, interaction with cargo, and motor activity. The ubiquitous co-factor nuclear distribution gene E (NudE) is implicated in many of dynein's functions, and mutations in NudE cause the brain developmental disease microcephaly. To identify genetic interactors of the Caenorhabditis elegans NudE homolog nud-2, we performed a genome-wide RNAi screen with the null allele nud-2(ok949), which compromises dynein function but leaves animals viable and fertile. Using bacterial feeding to deliver dsRNAs in a 96-well liquid format and a semi-automated fluorescence microscopy approach for counting parents and progeny, we screened 19762 bacterial clones and identified 38 genes whose inhibition caused enhanced lethality in nud-2(ok949) relative to the nud-2(+) control. Further study of these genes, many of which participate in cell division, promises to provide insight into the function and regulation of dynein.

Exploring Potential Germline-Associated Roles of the TRIM-NHL Protein NHL-2 Through RNAi Screening

TRIM-NHL proteins are highly conserved regulators of developmental pathways in vertebrates and invertebrates. The TRIM-NHL family member NHL-2 in Caenorhabditis elegans functions as a miRNA cofactor to regulate developmental timing. Similar regulatory roles have been reported in other model systems, with the mammalian ortholog in mice, TRIM32, contributing to muscle and neuronal cell proliferation via miRNA activity. Given the interest associated with TRIM-NHL family proteins, we aimed to further investigate the role of NHL-2 in C. elegans development by using a synthetic RNAi screening approach. Using the ORFeome library, we knocked down 11,942 genes in wild-type animals and nhl-2 null mutants. In total, we identified 42 genes that produced strong reproductive synthetic phenotypes when knocked down in nhl-2 null mutants, with little or no change when knocked down in wild-type animals. These included genes associated with transcriptional processes, chromosomal integrity, and key cofactors of the germline small 22G RNA pathway.

A novel chromosome segregation mechanism during female meiosis

During conventional anaphase A, chromosomes move outward toward spindle poles. Caenorhabditis elegans meiotic spindle poles move inward toward chromosomes to achieve the same end.

In a wide range of eukaryotes, chromosome segregation occurs through anaphase A, in which chromosomes move toward stationary spindle poles, anaphase B, in which chromosomes move at the same velocity as outwardly moving spindle poles, or both. In contrast, Caenorhabditis elegans female meiotic spindles initially shorten in the pole-to-pole axis such that spindle poles contact the outer kinetochore before the start of anaphase chromosome separation. Once the spindle pole-to-kinetochore contact has been made, the homologues of a 4-μm-long bivalent begin to separate. The spindle shortens an additional 0.5 μm until the chromosomes are embedded in the spindle poles. Chromosomes then separate at the same velocity as the spindle poles in an anaphase B–like movement. We conclude that the majority of meiotic chromosome movement is caused by shortening of the spindle to bring poles in contact with the chromosomes, followed by separation of chromosome-bound poles by outward sliding.

Prediction of Genetic Interactions Using Machine Learning and Network Properties

A genetic interaction (GI) is a type of interaction where the effect of one gene is modified by the effect of one or several other genes. These interactions are important for delineating functional relationships among genes and their corresponding proteins, as well as elucidating complex biological processes and diseases. An important type of GI - synthetic sickness or synthetic lethality - involves two or more genes, where the loss of either gene alone has little impact on cell viability, but the combined loss of all genes leads to a severe decrease in fitness (sickness) or cell death (lethality). The identification of GIs is an important problem for it can help delineate pathways, protein complexes, and regulatory dependencies. Synthetic lethal interactions have important clinical and biological significance, such as providing therapeutically exploitable weaknesses in tumors. While near systematic high-content screening for GIs is possible in single cell organisms such as yeast, the systematic discovery of GIs is extremely difficult in mammalian cells. Therefore, there is a great need for computational approaches to reliably predict GIs, including synthetic lethal interactions, in these organisms. Here, we review the state-of-the-art approaches, strategies, and rigorous evaluation methods for learning and predicting GIs, both under general (healthy/standard laboratory) conditions and under specific contexts, such as diseases.