Segmenting the genome by quantitative cellular descriptors using large-scale RNAi perturbations

1. Segmenting the genome by quantitative cellular descriptors using large-scale RNAi perturbations Florian Fuchs, Oleg Sklyar, Gregoire Pau, Christoph Budjan, Thomas Horn, Wolfgang Huber and Michael Boutros

2. Contents • Overview microscopy screen • Computational analysis + metrics optimization (Greg) • Microscopy retest (with Qiagen library, BD pathway) • Cell cycle analysis with drug treatment (Acumen) • DNA damage foci formation (Zeiss AxioImager)

3. Screening Procedure

4. Image analysis workflow

5. Classification and clustering of genetic phenoprints

6. Cell classifier and classifier training set Class M

7. Prediction rate vs. No. of descriptors

8. Metric optimization using STRING (Greg) score=quantile(d(i,j in STRING),0.1)/quantile(d(i,j in RANDOM),0.1

9. Metric optimization STRING: 59821 interaction pairs RANDOM: randomized version of STRING (nodes permutation)

10. Replicate analysis Pseudo-replicate siRNA comparison

11. Functional map edge if dist. < 0.1 38 clusters 1558 wells 32139 edges cyan – pos. control

12. Enrichment – hand-defined clusters • Find enrichment of GO and/or KEGG categories in a given cluster • Requirement: min. GO/KEGG terms size of 2, min. number of 2 genes per cluster belonging to the GO/KEGG category, p-value cut-off 1e-2 • 22 out of 38 clusters show enrichment in at least 1 GO category • e.g. chemotaxis, mitochondrion, regulation of cyclin-dependent protein kinase, cell cycle.

13. Enrichment – clusters defined by gene centers • Clusters based on a set of 29 genes of interest • e.g. CEP164, DONSON, CASP8AP2, CD3EAP, C20ORF4 • Radius of 30 closest genes to the gene of interest • Look for GO/KEGG enrichment in the 30 closest genes to these centers • Enrichment in e.g. centrosome, anti-apoptosis, mitosis, cell-cycle, proteasome

14. Donson - gene centered cluster 14 genes conserved in fly and worm

15. Donson gene centered cluster 30 closest genes to the center colored genes: GO enrichment

16. Microscopy retest Phenotypic readout (microscopy) with HeLa and U2OS • Individual single siRNAs (deconvolution of pools) • Pools from Qiagen (608) • Individual siRNAs from Ambion

17. Retest analysis of morphology screen Dharmacon retest Upgrade Validation on Phenotypic Level (56 Pools from Dharmacon) 4 % 13 % 24 % 20 % 39 % • Qiagen retest • 608 Genes were retested • 117 showed phenotype from global screen • additional 160 showed similar phenotype • Ambion single siRNA retest • 1 out of 2 plates finished • currently being analysed

18. Cell cycle analysis using Acumen Explorer Acumen eX3 • microplate cytometer for high-throughput in situ screening • applicable to a broad range of assays, e.g. • Cell cycle • Protein translocation • Cell proliferation • …

19. Cell cycle analysis using Acumen Explorer Plate formats: 96 to 1536 well plates in a high-throughput manner (25’ per 384 well plate) Laser: Up to 3 lasers – 405 nm (Hoechst, Alexa 405), 288 nm (PI, Alexa 488, FITC, eGFP), 633 nm (Alexa 633, Cy5) Features: Resolution similar to that achieved using a 20x microscope Field of view: 20x20mm (4 wells of a 96-well plate) => whole well scanning possible Multiplexing (up to 12 data channels)

20. Cell cycle analysis using Acumen Explorer Aim Identify genes involved in DNA damage signaling and/or are required for cell cycle progression Approach Downregulation of putative cell cycle regulatory proteins and drug treatment for induction of cell cycle arrest

21. Cell cycle analysis: protocol for Acumen

22. Comparison positive and negative controls HeLa (750 c/w seeded) 24 hr post-transfection siRluc 1500 cells/well G1: 59%, S: 10%, G2/M: 29% [Frequency] 5 10^4 10^5 1.5 10^5 2 10^5 [Intensity] HeLa (750 c/w seeded) 24 hr post-transfection siPlk1 650 cells/well G1: 11%, S: 7%, G2/M: 80% [Frequency] 5 10^4 10^5 1.5 10^5 2 10^5 [Intensity]

23. Well view after classification of nuclear content Classification of cells into G1, S and G2/M phase by determining the DNA content of the cell G1 S G2/M

24. The pseudo time-lapse experiments are reproducible 720 genes 3 replicates siRNA incubation for 24, 36, 48 hr Red dots: controls

25. Results pseudo time-lapse analysis

26. HU treatment causes cell cycle arrest [Frequency] [Intensity]

27. Results of HU treatment (time-lapse) 256 genes 48 hr siRNA +/- 24 hr HU + 0, 8, 16 or 24 hr release HeLa cell viablity phenotype after HU treatment

28. Results of HU treatment (time-lapse) 0 20 40 60 80 100 - HU

29. Results of HU treatment (time-lapse) 0 20 40 60 80 100 + HU

30. Microscopic analysis of DNA damage induction after siRNA treatment • Silencing of 24 target genes • 72 hr siRNA • 48 hr siRNA + 24 hr HU • 48 hr siRNA + 24 hr HU + 8 hr release • Staining of nucleus (Hoechst) and DNA-damage foci (anti-pH2AX) • Rluc, Top3a, Chek2, Clspn, Chek1, Casp8AP2, ERCC1, CDCA8, TMEM61, DLL4, Donson, ATM, CD3EAP, ATR, C20ORF4, PRIC285, SON, Rad17, RRMI, CADMI, Prim2A, WISPI, WDR33, Cep164

31. DNA damage pH2AX foci formation after 72 hr siRNA treatment (Zeiss AxioImager & Apotome, 63x-oil, deconvolution) DNA (Hoechst) α-pH2AX Rluc C20ORF4 Donson Donson

32. Donson depletion induces strong DNA damage foci formation (72 hr siRNA) DNA (Hoechst) α-pH2AX

33. CADM1 (cell adhesion molecule 1) May be involved in apoptosis, cell adhesion and regulation of cell cycle pH2AX-positive after release DNA (Hoechst) α-pH2AX 72 hr siRNA 48 hr siRNA + 24 hr HU + 8 hr release 48 hr siRNA + 24 hr HU

34. Outlook • Cloning of HA-tagged human Donson in pcDNA3.1 (o/e) • Generation of eGFP-tagged Donson fusion protein (pEGFP-C1), colocalization studies with known DNA damage markers • qPCR of single siRNAs of Donson (and others) • Cloning of mouse homolog of Donson in overexpression vector, rescue of Donson knockdown in human cells • Knockdown of fly homologs of Donson cluster in Drosophila cells, microscopy and cell-cycle (Acumen) analysis • Cell cycle analysis (Acumen) after IR irradiation & HU treatment in U2OS cells • Repeat DNA damage foci microscopy (replicate)