Whole genome functional analysis identifies novel components required for mitotic spindle integrity in human cells

Abstract

Background: The mitotic spindle is a complex mechanical apparatus required for accurate segregation of sister chromosomes during mitosis. We designed a genetic screen using automated microscopy to discover factors essential for mitotic progression. Using a RNA interference library of 49,164 double-stranded RNAs targeting 23,835 human genes, we performed a loss of function screen to look for small interfering RNAs that arrest cells in metaphase.

Results: Here we report the identification of genes that, when suppressed, result in structural defects in the mitotic spindle leading to bent, twisted, monopolar, or multipolar spindles, and cause cell cycle arrest. We further describe a novel analysis methodology for large-scale RNA interference datasets that relies on supervised clustering of these genes based on Gene Ontology, protein families, tissue expression, and protein-protein interactions.

Conclusion: This approach was utilized to classify functionally the identified genes in discrete mitotic processes. We confirmed the identity for a subset of these genes and examined more closely their mechanical role in spindle architecture.

Figure 1

Genome-wide library screen analyzed for mitotic spindle genes. (a) Outline for transfecting cells in 384-well microtiter plate format. Small interfering RNAs (siRNAs) are arrayed into 384-well microtiter plates (two siRNAs/well) and mixed with a lipid-based transfection reagent. Cell transfections are performed in a reverse or (retro)transfection manner, in which the cell culture is added to the preformed siRNA/lipid complexes and incubated at 37°C for 48 hours before -20°C methanol (MeOH) fixation. Indirect immunolocalization is used to fluorescently label cells in metaphase based on phospho-histone H3 (pHis) activity. HeLa cells were transfected in 384-well microtiter plates with 49,164 synthetic double-stranded RNAs (dsRNAs). Cells were also fluorescently labeled for α-tubulin (green), pHis (red), and DNA (blue) before being imaged on an automated microscope. (b) Plate normalized mitotic index values for the knock-down of 23,835 genes in duplicate are plotted on a Log2 scale. Calculated values are sorted in rank order (lowest to highest) and represented by the curve. Target genes with mitotic index values -2σ below the mean are shown in green. Genes with values 3σ above the mean are shown in magenta. Genes with values between the thresholds are shown in blue. Upper and lower dashed lines indicate scoring thresholds. A partial list of previously characterized genes having an essential role in chromosome segregation is given.

Figure 2

OPI clustering of high-content screening (HCS) results based on GO/IPR annotations. (a,b) Ontology-based pattern identification (OPI) heat map for each of the morphologic properties recorded in the microscopy based screen. Each row represents a Gene Ontology (GO)/InterPro group consisting of a significant number of annotated genes that shared the representative morphologic profile (P ≤ 0.05). Red and green color represents high and low scores in the corresponding morphological parameters. Headings symbolize morphologic parameters for mitotic index (MI), cell count (CC), nuclear roundness (NR), cell shape (CS), multinucleation (MN), and spindle intensity (SI). Red bars in the PPI and TA columns represent statistically significant support for the gene group based on protein-protein interaction (PPI) and tissue expression (TA) databases; these are determined based on OPI meta-analyses exhibiting multiple protein interactions or mRNA co-expression across 79 tissue samples, respectively. Groups shown in red contain known mitotic or spindle regulation genes, whereas those shown in green contain interesting novel components.

Figure 3

Validation of siRNA sequences for essential mitotic genes. (a) Protein-protein interaction (PPI) network for candidate genes in which at least one direct interaction (red lines) or indirect interaction (green lines) was identified. The cell cycle phases, based on previous expression analysis, are mapped on each protein bubble based on color. (b) PPI network for SON DNA/RNA-binding protein identified a number of novel components. Proteins in red squares, validated in our follow-up studies, included KIAA1604, FLJ13111/CENP-T, SON, and SMU-1. The green squares represent the nuclear factor-κB proteins examined elsewhere [25].

Figure 4

Cell cycle validation of isolated genes. (a) Quantitative comparison of mitotic index values based on phospho-histone H3 (pHis) detection in HeLa and U2OS cell lines. (b) Proliferation analysis. Cell counts after 48 hours of small interfering RNA (siRNA) incubation are determined and proliferation is reported as the ratio of cell counts compared with those from the negative control. (c) mRNA knockdown levels were determined using quantitative polymerase chain reaction and are reported as a percentage of target mRNA when cells are transfected with a negative control siRNA. (d) Cell cycle analysis of HeLa cells treated with siRNAs to determine relative G1, S, and G2/M cells per candidate gene validation using flowcytometry.

Figure 5

Spindle defects observed for RNAi phenotypes using confocal fluorescence microscopy. Cells transfected with single (double-stranded) small interfering RNA targeting (a) KIAA1604, (b) KIAA1569/Cep192, (c) FLJ10460/Cep27, (d) SON, (e) KIAA1160, (f) FLJ13111/CENP-T, (g) SMU-1, (h) C18orf24/SKA1, and (i) negative control. Cells were stained for α-tubulin (green), phospho-histone H3 (pHis; blue), and the CREST protein (red). Scale bar represents 5 μm.

Figure 6

Analyzing the role of SKA1 in MT dynamics. (a) DUF1395 domain sequence comparison showing highly conserved amino acids (red) across multiple organisms: CAB82670 (Arabidopsis thaliana), XP_478114 (Oryza sativa), CAA21578 (Caenorhabditis elegans), CAE58950 (Caenorhabditis briggsae), AAH15705 (Homo sapiens), XP_512132 (Pan troglodytes), XP_548812 (Canis familiaris), XP_584361 (Bos Taurus), BAB28731 (Mus musculus), NP_079857 (Mus musculus), XP_214527 (Rattus norvegicus), AAH76006 (Danio rerio), and XP_553928 (Anopheles gambiae str). (b) Time-lapse microscopy monitoring spindle assembly in U2OS cells for 2,100 seconds. Scale bar: 3 μm. Panels c to f show green fluorescent protein (GFP)-SKA1 localization in (c) metaphase, (d) anaphase, and (e,f) interphase. (f) Localization of GFP-SKA1 in interphase cells over-expressing GFP-SKA1 for more than 24 hours. Scale bar: 5 μm. Panels g and h show GFP-SKA1 localization in transfected HeLa cell (g) before and (h) 30 minutes after 10 μmol/l nocodozole treatment; (i,j) negative control images. Scale bar: 5 μm. (k) Model for SKA1's role in maintaining spindle integrity. SKA1 bundles microtubules (MT) and generates thicker and stronger fibers. Therefore, it prevents the loss of the spindle integrity before onsent of anaphase. Loss of this activity results in aberrant spindles with more than two poles.