Multiomic Analysis of the UV-Induced DNA Damage Response

Abstract

In order to facilitate the identification of factors and pathways in the cellular response to UV-induced DNA damage, several descriptive proteomic screens and a functional genomics screen were performed in parallel. Numerous factors could be identified with high confidence when the screen results were superimposed and interpreted together, incorporating biological knowledge. A searchable database, bioLOGIC, which provides access to relevant information about a protein or process of interest, was established to host the results and facilitate data mining. Besides uncovering roles in the DNA damage response for numerous proteins and complexes, including Integrator, Cohesin, PHF3, ASC-1, SCAF4, SCAF8, and SCAF11, we uncovered a role for the poorly studied, melanoma-associated serine/threonine kinase 19 (STK19). Besides effectively uncovering relevant factors, the multiomic approach also provides a systems-wide overview of the diverse cellular processes connected to the transcription-related DNA damage response.

Graphical abstract

Figure 1

Graphical Overview of the Multiomic Approach to Charting the Transcription-Related DNA Damage Response UV-induced DNA damage has effects both at the local (“repairosome”) and the global level. The proteomic screens and the siRNA screen used to investigate the damage response are outlined. UV irradiation (30 J/m²) was used for all proteomic analysis, while 15 J/m² was used in the RNAi screen.

Figure 2

Effect of UV-Induced DNA Damage on the CSB and RNAPII Interactomes (A) Left: UV-induced CSB interactome, in the presence and absence of MG132 as indicated. Right: enlargement of section indicated by box on the left. For clarity, only a few interesting proteins are indicated. Integrator subunits are labeled in yellow. (B) Western blots of CSB-Flag immunoprecipitation. The CSB-FLAG panel is duplicated to indicate that the panel rows belong to the same experiment. Note that CSB does not seem to enrich a specific, phosphorylated form of RNAPII (left panel). (C) The RNAPII interactome, in the presence of MG132. Some interesting proteins are indicated. Other proteins can be searched at http://www.biologic-db.org. See also Tables S1 and S2.

Figure 3

Effect of UV-Induced DNA Damage on the Chromatin Proteome, Ubiquitylome, and the Phosphoproteome (A) Left: effect of UV irradiation on the chromatin proteome in the presence and absence of MG132, as indicated. Right: enlargement of section indicated by box on the left. A few proteins are indicated. (B) As in (A), but for ubiquitylation. (C) As in (A) and (B), but phosphorylation. Other proteins can be searched at http://www.biologic-db.org. See also Tables S3, S4, and S5.

Figure 4

An siRNA Screen for Genes Affecting Transcription upon UV Irradiation (A) The experimental approach. (B) Typical examples of siRNAs that result in either (left) “low transcription,” or (right) “high transcription,” relative to the controls (middle). Different putative causes (not necessarily mutually exclusive) of the outcome are listed below arrows. (C) Nascent transcription profiles across a cell population in the absence of UV irradiation, and in the examples from (B), used to identify siRNAs giving rise to low and high transcription, respectively. EU intensity (y axis) across the population of cells in an individual plate well (x axis) is shown. (D) Graphical representation of the screen result. High transcribers are labeled green, and low transcribers are red. Specific genes are indicated. Other proteins can be searched at http://www.biologic-db.org.

Figure 5

Enriching the Phosphoproteome with Results from the Other Screens (A) Proteins that interact with CDK9 (pTEFb) and that become phosphorylated upon UV irradiation. Proteins are labeled increasingly blue with increasing phosphorylation. Proteins that scored in the RNAi screen, (squares with red border), interacted with RNAPII (small green spheres under name), interacted with CSB (red spheres), or became ubiquitylated upon UV irradiation (yellow “•Ub”) are indicated. Examples of CSB or RNAPII interactions that increased (black circle around spheres) or decreased (yellow circle around spheres) upon UV irradiation are also specified. (B) As in (A), but for proteins that interact with SRPK1.

Figure 6

Proteins and Processes that Score Highly in the Multiomic Screening Approach (A) Bar graph showing the number of proteins that scored above the Z score threshold in one or more screen. (B) Distribution of hits using aggregated Z scores. (C) As in (B), but with TC-NER score weighting. In (B) and (C), the colored wheels indicate relative weighting of scores from individual screens (see Figure S1A). Names and dots in red are examples from the TC-NER training category (“TCR”). Please note that, for clarity, even if a candidate scores highly in several scoring schemes, it is typically only indicated once. (D) Biased list of interesting proteins and protein complexes that scored highly. (E) Proteins from the TC-NER training category that scored above the Z score threshold (indicated by red bar) in screens across the multiomic approach (see Figure S1B). See also Figures S2, S3, and S4.

Figure 7

Involvement of STK19 in the Transcription-Related DNA Damage Response (A and B) Lack of normal transcription recovery in cells lacking STK19. (C–E) Cells lacking STK19 are UV-sensitive. The individual siRNAs that knock down STK19 (D) also give rise to UV sensitivity (E). The result of CSB knockdown is shown for comparison. NT, non-targeting siRNA. (F) Recruitment of GFP-tagged STK19 to DNA damage induced by laser micro-irradiation in a diffraction-limited spot (blue arrows) or stripe (yellow arrows). Cells were imaged immediately before and 2 hr after micro-irradiation. See also Figures S4 and S5 and the Supplemental Experimental Procedures for details.