Genomic locus proteomic screening identifies the NF-κB signaling pathway components NFκB1 and IKBKG as transcriptional regulators of Ripk3 in endothelial cells.

The receptor-interacting protein kinase 3 (RIPK3) is a multi-functional protein best known for facilitating cellular necroptosis and inflammation. Recent evidence from our lab indicates that RIPK3 expression must be tightly regulated in endothelial cells to promote angiogenesis, to maintain vascular integrity during embryogenesis, and to provide protection from postnatal atherosclerosis. RIPK3 activity and stability are regulated by post-translational modifications and caspase-dependent cleavage. However, less is known about the transcriptional regulation of Ripk3. Here we utilized an unbiased CRISPR-based technology called genomic locus proteomics (GLoPro) to screen transcription factors and coregulatory proteins associated with the Ripk3 locus in a murine endothelial cell line. We found that 41 nuclear proteins are specifically enriched at the Ripk3 locus, including the Nuclear Factor kappa-light-chain-enhancer of activated B cells (NF-κB) signaling pathway components NFκB1 and IKBKG. We further verified that NFκB1 and IKBKG directly bind the Ripk3 promoter and prevent TNFα-induced Ripk3 transcription in cultured human primary endothelial cells. Moreover, NFκB1 prevents RIPK3-mediated death of primary endothelial cells. These data provide new insights into NF-κB signaling and Ripk3 transcriptional regulation in endothelial cells.

Introduction

RIPK3 is a member of the receptor-interacting protein kinase (RIP) family of Ser/Thr protein kinases [1]. This broadly expressed protein is a critical executioner kinase in the necroptosis programmed cell death pathway [2]. RIPK3 also promotes inflammation through both kinase-dependent and -independent mechanisms [3-5]. Notably, overexpression of RIPK3 in various cell types can promote cell death and inflammatory cytokine production [6-9]. We recently reported that the chromatin-remodeling enzyme CHD4 suppresses Ripk3 expression in hypoxic murine embryonic endothelial cells (ECs) and that excessive RIPK3 expression in Chd4-deficient ECs contributes to lethal vascular rupture [10]. Interestingly, this RIPK3-mediated vascular rupture is not obviously linked to EC necroptosis or inflammation, indicating that aberrant RIPK3 expression can contribute to other damaging processes in ECs. Conversely, genetic deletion of endothelial Ripk3 impairs developmental angiogenesis [11] and exacerbates vascular lesion formation in a murine atherosclerosis model [12]. Therefore, endothelial RIPK3 expression must be tightly regulated to maintain vascular integrity, function, and homeostasis at different stages of life.

The activity and stability of RIPK3 are controlled by caspase-dependent cleavage and by various post-translational modifications, including phosphorylation, ubiquitination, and glycosylation [13-16]. However, little is known about the transcriptional regulation of Ripk3 in any cell type, other than its repression by CHD4 and by hypoxia-inducible factor 1 (HIF-1) in hypoxic ECs [10], its repression by CHD4 in muscle stem cells [17], and its methylation-dependent repression and promotion by the transcription factor SP1 in tumor cells [18,19]. Therefore, we sought to identify transcriptional regulators of Ripk3 in this study, and we chose to perform our screen in ECs because of our interest in the detrimental impact of misregulated RIPK3 expression on embryonic and postnatal vasculature.

Chromatin immunoprecipitation (ChIP) is an invaluable technique for identifying genetic targets of known transcriptional regulatory proteins. However, ChIP is not useful for identifying unknown transcriptional regulatory proteins that interact with a specific genomic locus. By contrast, genomic locus proteomics (GLoPro) is a newly reported and unbiased technique, which combines CRISPR-based genome targeting, proximity biotin-labeling, and quantitative proteomics to identify multiple proteins associated with a predefined genomic locus in living cells [20]. Here we utilized GLoPro technology to screen for transcription factors and coregulatory proteins associated with the Ripk3 locus in a cultured murine EC line, and we validated two of our findings—members of the NF-κB signaling pathway—in primary human ECs.

The NF-κB signaling pathway balances fundamental cellular survival and pro-inflammatory responses in a variety of cell types and is comprised of multiple transcription factor subunits and cytoplasmic proteins that regulate their nuclear translocation [21]. Activation of canonical NF-κB signaling can be triggered by inflammatory stimuli such as lipopolysaccharides (LPS), tumor necrosis factor α (TNFα), or interleukin-1β [22]. In ECs, a major consequence of NF-κB signaling activation is the robust expression of adhesion molecules that mediate the capture and extravasation of inflammatory cells from the circulation and into underlying tissues [23]. Importantly, NF-κB signaling also promotes EC survival under inflammatory conditions, which counterbalances the pro-permeability effects of cytokines and prevents catastrophic hemorrhage [24]. Our following discovery that members of the NF-κB signaling pathway transcriptionally regulate Ripk3 expression in stimulated ECs provides new insights into the relationship between NF-κB and RIPK3 and their known roles at the intersection between inflammatory and cell death pathways.

Materials and methods

Cell culture

The MS1 adult murine pancreatic endothelial cell line (ATCC) was maintained at 37°C and 5% CO2 in Dulbecco’s Modified Eagle Medium (DMEM) containing 5% fetal bovine serum. Authentication of the MS1 line was performed by ATCC, and the sex of MS1 cells is unknown, according to the ATCC manual. MS1 cells were electroporated with the iCaspex plasmid using a Gene Pulser II system (BioRad; 250 V, 500 uF) in serum-free OptiMEM (Invitrogen). After iCaspex electroporation, clonal selection was performed for 2 weeks under 2μg/mL puromycin. Single colonies were picked and tested for doxycycline inducibility by GFP expression. HEK293T cells were used for lentivirus production and were cultured at 37°C and 5% CO2 in DMEM containing 10% fetal bovine serum. Plasmids encoding gRNAs, gag, pol, tat, or VSVG were transfected into HEK293T cells with polyethylenimine. Two days later, cell culture supernatants containing lentivirus were collected and filtered through a 0.45 μm filter. sgRNA lentiviruses were transduced into MS1-Caspex cells in the presence of 10 μg/mL polybrene and were selected for stable incorporation after growth in 400 μg/mL hygromycin for 2 weeks. HUVECs (ATCC) were cultured in EBM-2 media supplemented with EGM and 10% fetal bovine serum according to the manufacturer’s recommendation (Lonza). All HUVECs used in this study were analyzed at passage 4–6. For siRNA-mediated gene knockdown, HUVECs were transfected with NFκB1 siRNA oligos (Thermo Fisher Scientific; #s9505), IKBKG siRNA oligos (Thermo Fisher Scientific; #s16186), RIPK3 siRNA oligos (Thermo Fisher Scientific; #136148 or #110923), or non-specific controls siRNA oligos (Thermo Fisher Scientific; #4390844) using Lipofectamine RNAiMAX reagent (Thermo Fisher Scientific) according to the manufacturer’s protocol.

Plasmid construction

sgRNA oligonucleotides targeting the promoter of murine Ripk3 were designed using the Broad Institute GPP Web Portal and were cloned into the pLenti SpBsmBI sgRNA Hygro plasmid. Cloning primers are listed in S6 Table. Plasmids are listed in S9 Table. All modified plasmids were subjected to DNA sequencing for verification. All constructs were prepared using Maxi Prep kits (Qiagen).

MS1 RIPK3 knockout (KO) cell line generation

RIPK3-KO MS1 cells were generated with CRISPR/Cas9 technology. Briefly, sgRNAs targeting the coding region of Ripk3 (S6 Table) were designed using the CHOPCHOP website and cloned into the CRISPR plasmid pSpCas9 (BB)-2A-GFP via the BbsI site. GFP-positive cells were sorted into a 96-well plate at a density of 1 cell per well with a FacsAria IIIu cell sorter (BD Biosciences). After the colonies were expanded, RIPK3 KO was validated by immunoblotting.

Immunoblots

Cells were lysed in RIPA buffer with Protease Inhibitor Cocktail (Thermo Fisher Scientific). Protein concentration was determined using the Pierce BCA Protein Assay Kit. Protein was electrophoresed on a 10% SDS-PAGE gel and then transferred to a PVDF membrane that was blocked in 5% nonfat dry milk-TBST for 1 hr. Primary antibodies (diluted in 5% milk-TBST) were incubated at 4°C overnight with gentle agitation, and membranes were then washed three times (15 min each) in TBST. HRP-conjugated secondary antibodies (diluted in 5% milk-TBST) were applied at room temperature for 1 hr with gentle agitation, and membranes were then washed five times (15 min each) in TBST. Secondary antibodies were detected using ECL western blotting detection reagents. All antibodies are listed in S5 Table.

Cell death analysis

Floating and attached HUVECs were harvested and centrifuged at 350 g for 5 min. Cells were then incubated with propidium iodide (BD Pharmingen) on ice for 1 min in the dark. Flow cytometric analysis was performed with a BD FACSCelesta flow cytometer.

Enrichment of biotinylated proteins for LC-MS/MS

Four T175 flasks of each sgRNA-dCas9-APEX2 EC line (~1X108 cells per line) and four flasks of the non-targeting gRNA (negative control) were grown for proteomic experiments. 500 ng/mL doxycycline was added to the cell culture media for 24 hours to induce the expression of dCas9-APEX2. Subsequently, 500 μm biotin tyramide phenol (APExBIO) in DMSO was added directly to the cell culture media. After 30 minutes, 1mM hydrogen peroxide was added to the media to induce biotinylation. After 60 seconds of very gentle swirling, the media was discarded, and the cells were washed three times with ice cold PBS containing 100 mM sodium azide and 100 mM sodium ascorbate. Cells were scraped and pelleted in 15 ml Falcon tubes with ice cold PBS. Biotinylated whole cell pellets were lysed with RIPA (50 mM TRIS pH 8.0, 1% Triton X-100, 1% sodium deoxycholate, 0.1% sodium dodecyl sulfate, and 150 mM NaCl) containing a protease inhibitor cocktail and sonicated to shear genomic DNA using a Misonix S-4000 sonicator (five 10 s pulses at an amplitude of 50). Whole cell lysates were clarified by centrifugation at 12,000g for 30 minutes at 4°C. Lysates of equal protein amounts from each gRNA line were incubated with 250 μL of a streptavidin magnetic bead slurry for 2 hours at 4°C and subsequently washed three times with cold lysis buffer. Bead-bound proteins were digested and subjected to subsequent LC-MS/MS analysis. Each protein sample was analyzed using three replicate LC-MS/MS analyses on a Fusion model quadrupole-Orbitrap mass spectrometer equipped with an Easy-nLC 1200 UPLC system and a Nanospray Flex ion source (Thermo). Proteins were identified using the MaxQuant v1.6.2.10 to search the MS data against the Uniprot Mouse database. Protein hits were analyzed in Perseus 1.6.12.0 (Max Planck Institute of Biochemistry). The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium via the PRIDE partner repository with the dataset identified PXD025675.

Gene Ontology analyses

Gene Ontology (GO) analyses for enriched ‘biological process’ terms of high-stringency filtered protein candidates were performed using the web tool DAVID Bioinformatics Database v6.8 (https://david.ncifcrf.gov/tools.jsp) for the ‘GOTERM_BP_DIRECT’ category. The complete set of all murine genes was used as a background. The DAVID outputs are shown in Fig 3. For KEGG pathway analysis, high-stringency filtered protein candidates were subjected to the web tool g:Profiler and included a false discovery rate of P<0.05 after Benjamini-Hochberg correction for multiple comparisons.

Fig 3

IKBKG is primarily localized in the nuclei of HUVECs and suppresses Ripk3 transcription after TNFα treatment.

(A) HUVECs were treated with vehicle or TNFα (100 ng/mL) for 24 hr and subsequently immunostained for IKBKG (red). Cellular nuclei were counterstained with Hoechst (20 μg/mL; blue). Representative images of single confocal optical sections are shown. Scale bars: 50 μm. (B) HUVECs were transfected with nonspecific (NS) or IKBKG-specific siRNA oligos for 24 hr and were subsequently treated with vehicle (PBS) or TNFα (100 ng/mL) for 24 hr. Ripk3 transcripts were measured by qRT-PCR. Note that data generated from NS-siRNA-treated cells are identical to those shown in Fig 2A because the experiments were performed at the same time. Data from 3 independent experiments were combined and are presented as relative fold change. Data are presented as mean ± S.D. All statistics were calculated using a two-way ANOVA with a Tukey’s multiple comparisons test. (*) indicates statistical significance (p<0.05).

Quantitative Real-Time PCR (qRT-PCR)

Total RNA was isolated from MS1 cells or HUVECs using the RNeasy Mini kit (Qiagen). cDNA was prepared using the iSCRIPT™ Reverse Transcriptase Kit (Bio-Rad), and qRT-PCR was performed using 2X SYBR green qPCR master mix (Applied Biosystems) and the CFX96 Real-Time System (Bio-Rad) with gene-specific primers (S7 Table). The relative fold change in transcription was determined using the comparative CT method and three housekeeping genes as internal controls: Gapdh, Rn18s, and β-actin (Actb). Statistical differences were calculated in GraphPad Prism 8. Statistical analyses are detailed in the figure legends.

Immunocytochemistry

Approximately 2 X 104 HUVECs were seeded per well of a 24 well plate and cultured on coverslips. After 24 hr, media containing vehicle or TNFα (100 ng/mL) was added to each well and cultured for an additional 24 hr. Fixation was performed by adding a 1% PFA solution in 1X PBS to monolayers and incubating samples for 5 min at 37°C. Fixation was quenched by washing samples with a 0.5 M glycine solution (in 1X PBS) two times, 5 min each, at room temperature. Samples were permeabilized by incubating the monolayer with 0.1% Triton X-100 in 1X PBS for 10 min at room temperature. Samples were incubated with 3% BSA with 0.02% NaN3 in 1X PBS (3% BSA) for 1 hr at room temperature to block. Anti-IKBKG Ab was resuspended (1:250) in 3% BSA solution and incubated at 4°C for 16 hr. Samples were washed 3 times in cold 1X PBS and incubated with anti-rabbit Cy3 (1:500) and Hoechst 10 mg/mL (1:500) in 3% BSA for 1 hr at room temperature. Samples were washed 3 times with cold 1X PBS and mounted onto glass slides using Prolong Gold mounting media. Images were collected using a Nikon C2 Confocal microscope and analyzed using NIS-Elements software.

Chromatin immunoprecipitation assay

ChIP experiments were performed using the Active Motif ChIP-IT® Express Kit per manufacturer’s instructions. Briefly, 2.5 X 106 HUVECs were seeded in a 10 cm dish. Media containing vehicle (PBS) or TNFα (100 ng/mL) was added 24 hr later, and cells were cultured for an additional 24 hr. Samples were prepared by fixing the monolayer with 1% PFA in 1X PBS for 5 min at room temperature. Cells were washed for 5 min at room temperature with a 1X Glycine Solution to quench PFA. Plates were rinsed with ice cold 1X PBS, aspirated, and replaced with 5 mL of ice-cold Cell Scraping Solution. Cells were scraped and pelleted at 500 RCF for 10 min at 4°C. Cell pellets were resuspended in 1 mL of Lysis Buffer and incubated on ice for 30 min. Cells were Dounce homogenized (20 strokes) to release cell nuclei. Nuclei were pelleted by centrifugation (2,400 RCF) at 4°C for 10 min. The nuclei pellet was resuspended in 350 μL of Shearing Buffer and sonicated using a Misonix S-4000 sonicator (four 10 sec pulses with an amplitude of 50) to generate DNA fragments averaging 500 base pairs in length. Twenty micrograms of sheared chromatin were incubated with either 2 μg of IgG isotype control, anti-IKBKG, or anti-NFκB1 antibodies and incubated on an end-to-end rotator at 4°C overnight. Samples were washed, resuspended in 50 μL of elution buffer, and incubated for 15 min on an end-to-end rotator at room temperature. Samples were reverse cross-linked by adding 50 μL of Reverse Cross-Linking Buffer to the eluted chromatin and incubated at 95°C for 15 min. Protein was digested by adding Proteinase K (0.5 mg/mL) to each tube and incubated at 37°C for 1 hr. Putative IKBKG and NFκB1 interactions with the Ripk3 promoter were analyzed by quantitative PCR (qPCR). The final primer concentrations used to amplify the Ripk3 promoter were: 250 nM (for the -0.1 kb, -0.5 kb, and -1 kb regions) and 500 nM (for the -14 kb region). Primers used for ChIP-qPCR are listed in S8 Table.

Statistics

Results are presented as mean ± S.D. of n independent experiments (n is reported in the figure legends). Data normality was determined using the D’Agostino-Pearson omnibus test. Two-way ANOVA with a Tukey post hoc test was used to determine changes in HUVECs knocked down with nonspecific siRNA or gene of interest-specific siRNA after treatment with vehicle or TNFα or Z-VAD-FMK or NSA (Figs 2A, 2C, 2D and 3B). These analyses were chosen in order to compare two factors simultaneously: siRNAs and treatments. One-sample t and Wilcoxon test was used to determine fold-change of ChIP enrichment compared to the normalized negative IgG control (Fig 4A and 4B). These analyses were chosen for comparison of one variable (NFκB1 or IKBKG mean enrichment value) against the calculated IgG control enrichment level. Significance was determined by a P-value of 0.05 or less. All statistical analyses were achieved using GraphPad Prism8 software.

Fig 2

NFκB1 prevents TNFα-induced Ripk3 transcription and cell death in HUVECs.

(A, B) HUVECs were transfected with nonspecific (NS) or NFκB1-specific siRNA oligos for 24 hr and were subsequently treated with vehicle (PBS) or TNFα (100 ng/mL) for 24 hr. (A) Ripk3 transcripts were measured by qRT-PCR. Data from 3 independent experiments were combined and are presented as relative fold change. (B) A representative immunoblot (IB) for NFκB1, RIPK3, and GAPDH is shown. Normalized densitometric values for RIPK3 are shown below the blots. (C) HUVECs were transfected with nonspecific (NS), NFκB1-specific, and/or RIPK3-specific siRNA oligos for 24 hr and were subsequently treated with vehicle (PBS) or TNFα (100 ng/mL) for 24 hr. Propidium iodide positive (PI+) cells were analyzed by flow cytometry (Flow) and were graphed as % of total cells. Data from 3 independent experiments were combined. (D) HUVECs were transfected with nonspecific (NS) or NFκB1-specific siRNA oligos for 24 hr and were subsequently treated with vehicle (PBS), TNFα (100 ng/mL), Z-VAD-FMK (50 μM), or necrosulfonamide (NSA, 5 nM) for 24 hr. PI+ cells were analyzed by flow cytometry and graphed as % of total cells. Data from 2 to 3 independent experiments were combined. All quantified data are presented as mean ± S.D. All statistics were calculated using a two-way ANOVA with a Tukey’s multiple comparisons test. (*) indicates statistical significance (p<0.05).

Fig 4

NFκB1 and IKBKG bind to the Ripk3 promoter in HUVECs.

ChIP assays using antibodies against NFκB1, IKBKG, or against rabbit IgG (as a negative control) were performed in HUVECs. Prior to ChIP, HUVECs were treated with vehicle (PBS) or TNFα (100 ng/mL) for 24 hr (A and B, respectively). Immunoprecipitated DNA was isolated and measured by qPCR to determine whether NFκB1 and IKBKG bound the Ripk3 promoter at the regions indicated on the X-axes. Three sets of experiments were performed independently. Data are graphed as the average fold change of enrichment at the indicated sites compared to the normalized average of IgG (negative control antibody) enrichment at each of those sites (dotted line). Error bars represent S.D. All statistics were calculated using a one-sample t and Wilcoxon test. (*) indicates statistical significance (p<0.05).

Results

Genomic locus proteomics (GLoPro) reveals proteins associated with the Ripk3 locus in cultured ECs

Because cultured EC lines express varying levels of RIPK3 protein (S1 Fig), we chose an immortalized line with relatively high expression of RIPK3—the murine adult pancreatic MS1 EC line—in which to perform GLoPro and identify regulatory proteins that influence Ripk3 transcription. We first established MS1 cells stably expressing catalytically-dead RNA-guided nuclease Cas9 (dCas9) linked to the engineered ascorbic acid peroxidase (APEX2), which can mediate rapid biotin labeling of proximal proteins in living cells. Three single guide RNAs (sgRNA) targeting the Ripk3 locus were individually co-expressed with dCas9-APEX2 in separate lines. The sgRNAs were designed to target the following regions of the Ripk3 locus: 39 base pairs (bp) downstream (3’) of the transcription start site (TSS), 115 bp upstream (5’) of the TSS, and 261 bp 5’ of the TSS (respectively denoted as g39, g115, and g261, Fig 1A). Cells stably co-expressing a non-targeting sgRNA (NT-gRNA) and dCas9-APEX2 were also established as a negative control. After pre-incubation of cells with biotin-phenol and addition of hydrogen peroxide, APEX-mediated biotinylated proteins at the endothelial Ripk3 locus were enriched and subjected to detection by liquid chromatography-mass spectrometry (LC-MS/MS).

Fig 1

Genomic locus proteomics (GLoPro) reveals proteins associated with the Ripk3 locus in cultured ECs.

(A) Schematic of GLoPro labeling of the Ripk3 locus in the MS1 EC line. Three targeting sgRNAs (color-coded bars) were designed to guide dCas9-APEX2 to different sequences upstream and downstream of the Ripk3 transcription start site (black arrow). Once targeted, dCas9-APEX2 biotinylates (green circles) proximal proteins associated with the Ripk3 locus (gray shapes), which are subsequently enriched and identified by mass spectrometry. (B) Venn diagram showing the number of proteins identified by GLoPro using the three Ripk3-targeting sgRNAs (denoted as g39, g115, and g261) versus a non-targeting control sgRNA (denoted as NT-gRNA). See also S1 Table. (C) Heat map of high-stringency filtered GLoPro hits arranged by Log2 intensity. The 41 proteins listed were identified by all three Ripk3-targeting gRNAs and by annotated gene ontology (GO) terms including “nuclear as cellular component” and “transcription as molecular function.” NFκB1 and IKBKG (listed in red) were further analyzed for validation as Ripk3 transcriptional modulators (see Figs 2–4).

In total, we identified 2613 proteins with g39, 2296 proteins with g115, and 2266 proteins with g261. Among these, 197 proteins were detected by all three Ripk3-targeting sgRNAs but were not detected with the NT-gRNA control (Fig 1B and S1 Table). Since our goal was to identify new transcriptional regulators of Ripk3, these 197 proteins were further filtered to select for nuclear components and transcription factors according to gene ontology (GO) term annotation, which yielded 41 proteins (Fig 1C and S2 Table). Additional analysis of GO biological process enrichment among these 41 proteins revealed that they are related to processes such as transcription and transcript processing, regulation of DNA methylation, apoptosis, and positive regulation of NF-κB signaling (S2A Fig and S3 Table). KEGG Pathway Analysis of the 41 proteins likewise highlighted transcript processing (spliceosome), apoptosis, and various cellular differentiation processes that are linked to NF-κB signaling [21,25] (S2B Fig and S4 Table).

Identification of NFκB1 as a transcriptional regulator of Ripk3 in ECs

RIPK3 has been linked to the NF-κB signaling pathway in non-vascular contexts [3,4], but it has not yet been identified as a transcriptional target of NF-κB signaling. Therefore, we sought to validate the transcriptional regulation of Ripk3 by NFκB1, which was one of our 41 GLoPro hits (Fig 1C).

Since primary human umbilical vein endothelial cells (HUVECs) express low levels of RIPK3 at basal conditions (S1 Fig), we used them to explore the capacity for NFκB1 to stimulate Ripk3 transcription. Specifically, we took advantage of the robust NF-κB signaling response that the pro-inflammatory cytokine tumor necrosis factor-alpha (TNFα) elicits in HUVECs [26]. We found that NFκB1 knockdown did not alter Ripk3 transcription significantly in HUVECs maintained under basal conditions (Fig 2A). However, NFκB1 knockdown followed by TNFα stimulation resulted in a significant increase in Ripk3 transcripts (Fig 2A). NFκB1 knockdown also elevated RIPK3 protein levels in HUVECs cultured with or without TNFα stimulation (Fig 2B). Importantly, we found that NFκB1 knockdown caused significant cell death in HUVECs grown under basal conditions or with TNFα stimulation, and concomitant RIPK3 knockdown rescued this cell death under both conditions (Fig 2C). Moreover, the pan-caspase inhibitor Z-VAD-FMK significantly reduced the cell death observed in NFκB1 knockdown HUVECs treated with TNFα, while the necroptosis inhibitor necrosulfonamide (NSA) had no impact on this cell death (Fig 2D). These data indicate that the HUVEC death triggered by NFκB1 knockdown and TNFα treatment is mediated through a RIPK3- and caspase-dependent mechanism. Collectively, our in vitro data demonstrate that NFκB1 prevents TNFα-induced Ripk3 transcription and subsequent cell death in primary HUVECs.

Identification of IKBKG as an additional NF-κB signaling pathway component that transcriptionally regulates Ripk3 in ECs

In order to validate an additional target protein from our GLoPro screen (Fig 1C), we assessed the ability of IKBKG to impact Ripk3 transcription in HUVECs. IKBKG (also known as NEMO or IKK-γ) is widely expressed and best known for its cytoplasmic roles in activating the canonical NF-κB signaling pathway and protecting cells from TNFα-induced apoptosis [27,28]. Nevertheless, IKBKG can translocate to the nucleus under genotoxic stress conditions [29], which likely accounts for its GO term annotation as “nuclear as cellular component” among our GLoPro targets (Fig 1C). We first analyzed the cellular localization of IKBKG in HUVECs by performing immunocytochemistry on cells grown under basal conditions or stimulated for 24 hr with TNFα. We detected substantial nuclear staining of IKBKG in cells grown under both conditions. These localization data supported the idea that IKBKG could play a nuclear role in regulating Ripk3 transcription. We next analyzed Ripk3 transcripts in HUVECs depleted of IKBKG. We did not see a significant impact on Ripk3 transcripts when we knocked down IKBKG in HUVECs grown under basal conditions (Fig 3B). However, IKBKG knockdown followed by TNFα stimulation significantly increased Ripk3 transcripts in HUVECs (Fig 3B), similarly to NFκB1 knockdown with TNFα stimulation (Fig 2A).

NFκB1 and IKBKG bind to the Ripk3 promoter in HUVECs

Finally, in order to confirm that NFκB1 and IKBKG directly bind the Ripk3 promoter in ECs, we performed ChIP for these proteins in HUVECs. We found variable evidence for NFκB1 binding (p = 0.14) and significant evidence for IKBKG binding (p = 0.03) approximately 0.5 kb upstream (-0.5 kb) of the Ripk3 TSS in HUVECs grown under basal conditions (Fig 4A). However, after 24 hr of TNFα treatment, we saw increased binding of both proteins at a region approximately 1 kb upstream (-1.0 kb) of the Ripk3 TSS and significant additional binding of IKBKG closer to the TSS (-0.2 kb) (Fig 4B). Therefore, the NF-κB signaling pathway components NFκB1 and IKBKG undergo differential and increased binding to the Ripk3 promoter in HUVECs stimulated with TNFα, which likely contributes to their suppression of Ripk3 transcription under these conditions.

Discussion

RIPK3 is a pleiotropic protein with known roles in necroptotic and apoptotic cell death pathways, inflammasome activation, and aerobic metabolism [30-32]. Accordingly, changes in RIPK3 expression have been associated with a range of inflammatory diseases and cancers [33]. Because RIPK3 expression can impact its function, many studies have focused on how post-translational modifications impact RIPK3 stability, particularly in the context of immune cells [34,35]. Here we sought to complement these studies by providing new insights into Ripk3 transcriptional regulators. We designed our study to identify such regulators in ECs because our previous research indicates that endothelial RIPK3 expression levels impact vascular stability, angiogenesis, and anti-inflammatory properties [10-12]. Therefore, we reasoned that elucidation of transcriptional regulators of endothelial Ripk3 could provide new therapeutic targets for modulating vascular diseases.

The GLoPro technique that we employed here yielded 41 proteins associated with nuclear localization and/or transcription that reside near the Ripk3 TSS in immortalized MS1 ECs cultured under basal conditions. To address the biological relevance of this study, we utilized primary ECs to investigate the capacity of two of those proteins (NFκB1 and IKBKG) to influence Ripk3 transcription under basal and inflammatory stimulation conditions. The other 39 proteins that we identified remain untested and therefore provide opportunities for future examination. In addition, it would be interesting to build off our initial findings by assessing how endothelial Ripk3 transcriptional regulators change with additional stimuli. For example, we previously reported that the chromatin remodeling enzyme CHD4 only binds to the Ripk3 promoter and represses its transcription in embryonic ECs grown under hypoxic conditions [10]. Future GLoPro experiments performed on different subtypes of ECs or on ECs subjected to stimuli such as hypoxia, oxidatively modified lipoproteins, additional inflammatory cytokines, and reactive oxygen species could shed new insights into the transcriptional regulation of endothelial Ripk3 expression in various vascular disease contexts.

Multiple studies have demonstrated that RIPK3 can activate the NF-κB signaling pathway and subsequent cytokine production in monocytes, macrophages, and dendritic cells [3,4,36]. Our GLoPro screen and validation studies now demonstrate a reciprocal relationship likewise exists: NFκB1 and IKBKG can bind to the Ripk3 promoter and suppress Ripk3 transcription in TNFα-stimulated HUVECs. Moreover, we found that NFκB1 prevents RIPK3-mediated death of HUVECs following TNFα treatment. Since TNFα is a major inflammatory cytokine that is acutely produced when mice are challenged with the bacterial endotoxin LPS [37], it is interesting to note that mice with endothelial-specific inactivation of the NF-κB signaling pathway display LPS-induced vascular permeability and EC apoptosis [24]. However, mice exposed to more chronic, low-grade inflammation during atherosclerosis progression benefit from endothelial-specific inactivation of the NF-κB signaling pathway [38]. Therefore, we question whether TNFα dosage impacts the ability of NFκB1 and IKBKG to protect ECs from excessive endothelial Ripk3 expression and subsequent vascular damage in vivo. If so, RIPK3 might be a beneficial therapeutic target in vascular diseases associated with high TNFα levels such as sepsis.

NFκB1 is a known suppressor of transcription when its proteolytically processed subunits (p50) homodimerize and bind to promoters of NF-κB target genes [39]. Therefore, our discovery that NFκB1 binds the Ripk3 promoter in HUVECs and suppresses Ripk3 transcription and cell death following TNFα stimulation, implies that Ripk3 is directly transcriptionally repressed by p50 homodimers. However, p50 can also dimerize with other NF-κB transcription factors such as RelA, RelB, and c-Rel to promote transcription [40]. It is interesting to speculate that such heterodimers might promote Ripk3 transcription under conditions other than those used in this study. Notably, no positive regulators of Ripk3 transcription have yet been identified in ECs or other cell types.

Our discovery that IKBKG is also capable of binding the Ripk3 promoter and suppressing its transcription was a true surprise for us. This protein is best known for its cytoplasmic roles in promoting NF-κB signaling by facilitating the degradation of IKK proteins that otherwise prevent NF-κB transcription factors from translocating to the cell nucleus [27]. To our knowledge, nuclear roles for IKBKG have not yet been defined in ECs, so our detection of substantial IKBKG expression in the nuclei of HUVECs grown under basal or TNFα-stimulated conditions was unexpected. Likewise, the binding of IKBKG that we saw at the Ripk3 promoter implies that it plays a direct role in suppressing Ripk3 transcription following TNFα stimulation. These findings help validate our GLoPro screen for Ripk3 transcriptional regulators and pose additional questions about nuclear roles for IKBKG in ECs.

The GO terms associated with the proteins we found enriched at the Ripk3 locus in ECs speak to other interesting regulators and functions of RIPK3. For example, in addition to its well-known roles in the necroptotic cell death pathway, RIPK3 can also regulate apoptosis of fibroblasts and epithelial cells in specific contexts [41,42]. Since our GO term analyses highlight “apoptotic process” as a biological function associated with our GLoPro-generated proteins, RIPK3 may also have apoptotic capacity in ECs to complement its documented necroptotic roles in these cells [43]. Our HUVEC studies support this hypothesis, since the pan-caspase inhibitor Z-VAD-FMK rescued NFκB1-knockdown cells treated with TNFα from death, while the necroptosis inhibitor NSA did not (Fig 2D). In addition, the GO terms highlighting “brain development”, “positive regulation of neurogenesis”, and “long-term memory” are interesting to us, since some studies have implicated RIPK3 in central nervous system pathologies [44,45]. This correlation highlights a need to consider endothelial RIPK3 and its regulation in the context of brain development and diseases. Finally, methylation of the Ripk3 promoter has been proposed to contribute to tumorigenesis [19,46,47]. We found that several protein candidates associated with the endothelial Ripk3 locus are involved in histone and DNA methylation, including euchromatic histone-lysine N-methyltransferase 2 (EHMT2), methyl-CpG binding domain protein 3 (MBD3), and methyl CpG binding protein 2 (MECP2). Future investigation will be needed to determine how these proteins regulate Ripk3 expression in ECs and whether they impact RIPK3 function in the context of developmental and tumor angiogenesis.

In conclusion, our study provides a broad and unbiased view of transcriptional regulators found at the endothelial Ripk3 locus and highlights the varied and complex biological processes associated with RIPK3 function. We believe these findings can serve as a foundation for further analyses of Ripk3 transcriptional regulation and its cellular roles in both vascular and non-vascular contexts. Importantly this study also sheds new light on the relationship between the NF-κB pathway and RIPK3 at the intersection of cellular inflammation and cell death responses in ECs. Further studies will be required to assess whether NF-κB components likewise regulate Ripk3 expression in additional cell types.

(related to Results). RIPK3 protein levels vary in cultured ECs.

RIPK3 protein levels were analyzed by immunoblotting in immortalized MS1 ECs (adult murine pancreas-derived), immortalized C166 ECs (embryonic murine yolk sac-derived), and primary human umbilical vein endothelial cells (HUVECs). MS1 RIPK3 knockout (KO) ECs were generated by CRISPR/Cas9 technology and were included as a negative control. Note that the molecular weight (MW) of human RIPK3 is slightly greater than that of mouse RIPK3.

(TIF)

Click here for additional data file.

(related to Results). Additional annotation of filtered GLoPro hits reveals functional associations.

(A) Functional annotation clustering of GO terms associated with the 41 filtered Ripk3 GLoPro proteins shown in Fig 1C by DAVID. (B) Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis of the 41 filtered Ripk3 GLoPro proteins shown in Fig 1C. This analysis was performed using g:Profiler and included a false discovery rate of p<0.05 after Benjamini-Hochberg correction for multiple comparisons.

(TIF)

Click here for additional data file.

Related to Fig 1B; 197 proteins that were detected by all three Ripk3-targeting sgRNAs but that were not detected with the non-targeting sgRNA control.

(XLSX)

Click here for additional data file.

Related to Fig 1C; Annotation of GLoPro hits encompassing nuclear transcriptional regulators.

(XLSX)

Click here for additional data file.

Related to Fig 1C; GO biological process enrichment analysis of the 41 proteins.

(XLSX)

Click here for additional data file.

Related to Fig 1C; KEGG Pathway Analysis of the 41 proteins.

(XLSX)

Click here for additional data file.

(related to Materials and Methods). Key resources used in this study.

(DOCX)

Click here for additional data file.

(related to Materials and Methods). Cloning primers used in this study.

(DOCX)

Click here for additional data file.

(related to Materials and Methods). qRT-PCR primers used in this study.

(DOCX)

Click here for additional data file.

(related to Materials and Methods). ChIP-qPCR primers used in this study.

(DOCX)

Click here for additional data file.

(related to Materials and Methods). Plasmids used in this study.

(DOCX)

Click here for additional data file.

(TIF)

Click here for additional data file.

(DOCX)

Click here for additional data file.

10 Dec 2020

PONE-D-20-35540

Genomic locus proteomic screening identifies NF k B1 as a transcriptional regulator of Ripk3 in endothelial cells

PLOS ONE

Dr. Griffin,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

Some of the changes necessary for acceptance include: additional validation of targets obtained from the GloPro assay, addressing sensitivity of the assays [GloPro and the low RIPK3 protein levels in endothelial cells (ECs)] and the need for rigorous quantification of all data in the paper. In addition, all comments related to localization of RIPK3, and its functional relevance with NF-kb binding to its promoter, and the functional role of RIPK3 in ECs must be constructively addressed. The authors are also encouraged to provide additional bioinformatic and mutational data for the NF-kb binding sites on the promoter, as requested by the reviewer but this is not necessary for acceptance.

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Reviewer #3: Yes

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Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

**********

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Reviewer #3: Yes

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Reviewer #1: Although the manuscript was written well. There are few concerns to consider. Please see below for the clarifications.

1. RIPK3 is predominantly in the cytoplasm, by any means did the author assess the interaction is cytoplasmic or nuclear.

2. It is more concerning that if NFkB1 knockdown caused significant cell death in HUVECs grown under basal conditions or with TNF-a stimulation, when was the transcriptional and translational experiments done.

3. It implies that TNF-a only have transcriptional regulation of RIPK3 but not translational.

4. What is the rationale for using pan-caspase inhibitor Z-VAD-FMK to rescue NF-kB knockdown mediated cell death in HUVECs? It appears too vague.

5. If endothelial RIPK3 expression must be tightly regulated to maintain vascular integrity and homeostasis at different stages of life, the low-level expression of RIPK3 in HUVECs suggest HUVECs may not be the right model. Could you please clarify the rationale for using HUVECs?

6. In the discussion section, many studies have focused on how post-translational modifications impact RIPK3 stability, particularly in the context of immune cells, could you please give any references to that.

7. In the discussion section, according to the author, the study was designed to identify regulators such as RIPK3 in ECs, is HUVECs the right model to study such kind of regulator. The rationale is not clear.

8. In the discussion section some of the information about NF-kB can be moved to introduction.

Reviewer #2: Gao et al., have investigated, “Genomic locus proteomic screening identifies NFB1 as 1 a transcriptional regulator of Ripk3 in endothelial cells”. Authors have screened transcription factors and coregulatory proteins associated Ripk3 using GLoPro – CRISPR approach in MS1 and HUVEC cells. There are few issues that need to be addressed before publication as follows:

General:

1. The results section is poorly written and has not explained in depth to support their experimental conclusions.

2. Figure2, need better color contrast to observe heat map matrix. Secondly, Merge Figure 1 and 2.

3. Figure 3 panel A&B should be moved to Supplementary. It does not add any experimental parameters for the manuscript.

Specific Comments:

4. GLoPro – CRISPR approach/ screening is the backbone of the manuscript. Authors should validate more identified proteins as are listed in Figure 2. Simple heatmap is not enough for being a main manuscript Figure.

5. Supporting Figure S1 show that HUVEC cells have very low protein expression (~negligible) of RIPK3 as compared to MS1 cells, however, CHIP -IP assay, lane NFkB1 in Figure 4 panel A&B, do not co-relate. It is very important to have quantitative enrichment or fold change for each test samples with some Statistically Analysis.

6. Figure 5 panel B need quantification as well as more detail in result section. Why NFkB1 (p105/p50) is high? What are other bands at MW 105 and 50?

Reviewer #3: Gao et al perform Genomic Locus Proteome (GLoPro) screening to identify proteins that interact with the RIPK3 promoter in endothelial cells. By utilizing 3 sgRNA probes, they identify a number of overlapping proteins, including 41 nuclear proteins, some of which are transcription factors. One of these transcription factors, NF-kB1, binds the RIPK3 promoter in HUVEC by ChIP and inhibits RIPK3 expression in the presence of TNF-alpha. They furthermore show that knock-down of NF-kB1 induces cell death in a RIPK3-dependent manner. This is an interesting approach to identify potential regulators, but there are several limitations.

Major Comments:

1) What is the resolution of GLoPro? Would you anticipate that all three probes would identify the same interacting proteins? For the MS1 NF-kB1 ChIP data, it seems to only interact with a distal region (-1 kb), but the GLoPro showed interaction with all three probes, which were more proximal to the promoter. Is this due to differences in resolution between these two techniques?

2) Are there cis elements in the RIPK3 promoter that match the transcription factors that were identified? This is especially relevant for NF-kB1. Where are the NF-kB elements and is the binding predicted to be conserved across species? Does mutation of NF-kB motifs affect promoter activity in a luciferase assay?

3) It would be helpful if there was additional validation of the GLoPro technique beyond just NF-kB1.

4) Does NF-kB1 knock-down in MS1 cells affect RIPK3 expression?

Minor Comments:

1) It isn’t clear how the control probe was designed.

2) Are the GO terms shown in the figures complete or selected GO terms? This should be indicated in the figure legends.

3) Information on the number of replicates that were performed should be included in the figure legends.

4) In Figure 2, it would be helpful to show the data from the control oligo in the heat map for comparison purposes.

**********

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Reviewer #1: Yes: KARTHIKEYAN THIRUGNANAM

Reviewer #2: No

Reviewer #3: No

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4 May 2021

Please see the attached "Response to Reviewers" for our full response (including figures)

April 28, 2021

Ramani Ramchandran

Academic Editor

PLOS ONE

RE: Resubmission of PONE-D-20-35540

Dear Dr. Ramchandran:

Thank you for handling the recent reviews of our manuscript “Genomic locus proteomic screening identifies NF�B1 as a transcriptional regulator of Ripk3 in endothelial cells.” We appreciated the Re-viewers’ constructive critiques and have generated new data and re-written/organized sections of our original manuscript to address their queries, as detailed below.

Reviewer #1

1. “RIPK3 is predominantly in the cytoplasm, by any means did the author assess the interaction is cytoplasmic or nuclear.”

We agree with the Reviewer that RIPK3 is predominantly a cytoplasmic protein in cell types that have been assessed for its localization. Because the goal of this manuscript was to identify tran-scriptional regulators of Ripk3, the genomic locus proteomic (GLoPro) screen that we utilized here was performed to identify proteins that interact with the Ripk3 promoter—not with RIPK3 protein itself. Nevertheless, we recently performed an unbiased proteomic screen to identify RIPK3-interacting proteins in both HUVECs and the MS1 endothelial cell line [1]. NF�B1 and IKBKG (newly analyzed in this revision) did not emerge in our mass spectrometry analysis of proteins that immunoprecipitated with RIPK3 in these endothelial cell lines. Therefore, our collec-tive data indicate that NF�B1 and IKBKG interact with the Ripk3 promoter in endothelial cells but not with RIPK3 protein itself.

2. “It is more concerning that if NF�B1 knockdown caused significant cell death in HUVECs grown under basal conditions or with TNF� stimulation, when was the transcriptional and translational experiments done?”

RIPK3 transcriptional and translational experiments (original Figures 5A and 5B; revised Figures 2A and 2B, respectively) were performed at 48 hr (24 hr after NF�B1 knockdown plus 24 hr after additional vehicle or TNF� treatment). This is comparable to the timecourse of analysis for cell death (original Figures 5C and 5D; revised Figures 2C and 2D). Please note that we routinely rinse cultured cells before all analyses to remove dead cells and debris. Moreover, transcription is evaluated by qPCR using three housekeeping genes as internal controls, and GAPDH is used as a loading control for our western blots. Therefore, we are confident that we are measuring Ripk3 transcripts and protein in live cells rather than dead ones.

3. “It implies that TNF� only have transcriptional regulation of RIPK3 but not translational.”

TNF� treatment has a small impact on Ripk3 transcription (original Figure 5A; revised Figure 2A, lanes 1 vs. 3: p=0.28) and translation (original Figure 5B; revised Figure 2A, lanes 1 vs. 3), but a bigger impact when combined with NF�B1 knockdown (original Figure 5A and 5B; revised Fig-ures 2A and 2B, lanes 1 vs. 4). Admittedly, the transcriptional impact of this combination is great-er than the translational impact (8.2-fold transcriptional change vs. 2.6-fold translational change). Nevertheless, the functional relevance of TNF� treatment plus NF�B1 knockdown is evident from the cell death assays (original Figure 5C; revised Figure 2C, lane 6) (original Figure 5D; re-vised Figure 2D, lane 4).

4. “What is the rationale for using pan-caspase inhibitor Z-VAD-FMK to rescue NF�B1 knockdown mediated cell death in HUVECS? It appears too vague.”

Z-VAD-FMK is a pan-caspase inhibitor that has been used since the mid-1990s to block pro-grammed cell death in a variety of mammalian cell lines [2]. It is commonly employed to distin-guish apoptosis from non-caspase-mediated forms of cell death such as necroptosis [3]. Z-VAD-FMK is also frequently used in combination with TNF� stimulation to block apoptosis and drive cultured cells toward RIPK3-dependent necroptosis [4, 5]. When we determined that the elevated cell death we detected in HUVECs treated with TNF� and NF�B1 knockdown was RIPK3-dependent (original Figure 5C; revised Figure 2C, lanes 6 vs. 8), we assumed the death would be mechanistically necroptotic rather than apoptotic. Therefore, we predicted that we would be able to block the cell death with the necroptosis inhibitor necrosulfonamide (NSA) but not with the apoptosis inhibitor Z-VAD-FMK. However, our cell death blocking experiments gave the opposite results (original Figure 5D; revised Figure 2D), indicating that the RIPK3-mediated death we stimulated in HUVECs was apoptotic and/or caspase-dependent rather than necroptotic. This result adds to our lab’s growing evidence that RIPK3-mediated necroptosis is difficult to stimulate or detect in endothelial cells both in vitro and in vivo [6, 7].

5. “If endothelial RIPK3 expression must be tightly regulated to maintain vascular integrity and ho-meostasis at different stages of life, the low-level expression of RIPK3 in HUVECs suggest HU-VECs may not be the right model. Could you please clarify the rationale for using HUVECs?”

Although the immortalized MS1 endothelial cell line we used for the GLoPro studies was critical for generating the large number of cells required for this assay, we believe that HUVECs are more appropriate for functional validation studies since they are primary cells and are maintained at low passage number (endothelial cells are notoriously plastic and prone to de-differentiation in prolonged culture[8]). Notably, HUVECs are responsive to TNF�-mediated NF-�B activation and downstream signaling events [9], which makes them particularly relevant to this study. In addi-tion, we recently used HUVECs to study novel angiogenic roles for RIPK3, and they faithfully re-capitulated endothelial cell behaviors that occurred upon Ripk3 genetic deletion in vivo [1]. There-fore, although RIPK3 is expressed at relatively low levels in unstimulated HUVECs compared to immortalized endothelial cells (see Figure S1), RIPK3 is clearly functional and biologically rele-vant in HUVECs and requires regulated maintenance.

6. “In the discussion section, many studies have focused on how post-translational modifications impact RIPK3 stability, particularly in the context of immune cells, could you please give any ref-erences to that.”

We have added relevant references, as requested (see new references #34, 35). Please see al-so references #13-16, which were previously cited in our Introduction.

7. “In the discussion section, according to the author, the study was designed to identify regulators such as RIPK3 in ECs, is HUVEC the right model to study such kind of regulator. The rationale is not clear.”

Please see our response to #5 above.

8. “In the discussion section some of the information about NF-�B can be moved to introduction.”

We have moved background information about NF-�B signaling in ECs to the introduction, as suggested.

Reviewer #2

1. “The results section is poorly written and has not explained in depth to support their experimental conclusions.”

We have revised the Results section to clarify the techniques and motivations behind all the ex-periments.

2. “Figure 2 need better color contrast to observe heat map matrix. Secondly, merge Figure 1 and 2.”

We have revised and merged Figures 1 and 2, as suggested.

3. “Figure 3 should be moved to Supplementary. It does not add any experimental parameters for the manuscript.”

The original Figure 3 is now Figure S2, as suggested.

4. “GLoPro-CRISPR approach/screening is the backbone of the manuscript. Authors should vali-date more identified proteins as are listed in Figure 2.”

We appreciated this important recommendation and have now evaluated IKBKG (also known as NEMO or IKK-�) for its ability to bind the Ripk3 promoter and regulate its transcription. We chose this protein among those gleaned from the GLoPro screen because of its important role in the NF-�B signaling pathway, which is a critical component of our manuscript. Notably, IKBKG is best known for its cytoplasmic roles in activating the NF-�B pathway and in protecting cells from TNF�-induced apoptosis [10, 11]. However, IKBKG can also undergo nuclear translocation upon stress induction in a pre-B cell line [12]. Interestingly, we now show that IKBKG is primarily ex-pressed in the nuclei of HUVECs grown under basal conditions, and its nuclear expression ap-pears to be further elevated upon TNF� treatment (see revised Figure 3A). Importantly, knock-down of IKBKG significantly elevates Ripk3 transcription in TNF�-treated HUVECs (see revised Figure 3B, lane 4)—similarly to the Ripk3 elevation seen with NF�B1 knockdown plus TNF� treatment (revised Figure 2A, lane 4)—which indicates that both of these NF-�B pathway com-ponents suppress endothelial Ripk3 transcription upon TNF� treatment. Importantly, our ability to ChIP IKBKG to the Ripk3 promoter in HUVECs grown under basal conditions (revised Figure 4A, lane 4) and to detect its recruitment to the -0.2 kb and -1.0 kb sites of the promoter after TNF� treatment (revised Figure 4B, lanes 2 and 6) support our conclusion that IKBKG directly regu-lates Ripk3 transcription in HUVECs, particularly after TNF� treatment. These new ChIP, im-munostaining, and transcriptional data further validate our GLoPro approach while also providing novel insights into nuclear roles for IKBKG in endothelial cells.

5. “Supporting Figure S1 show that HUVEC cells have very low protein expression (~negligible) of RIPK3 as compared to MS1 cells, however, ChIP assay, lane NF�B1 in Figure 4 panel A & B, do not co-relate. It is very important to have quantitative enrichment or fold change for each test samples with some Statistically Analysis.”

To address this important request, we repeated all our HUVEC ChIP analyses in triplicate and have analyzed the data by qPCR for quantitative analysis of NF�B1 and IKBKG enrichment at the Ripk3 promoter (see revised Figure 4). Also, please see responses to Reviewer 1 (#3 and #5) about Ripk3 transcript vs. protein levels in HUVECs

6. “Figure 5 panel B need quantification as well as more detail in result section. Why NFkB1 (p105/p50) is high? What are other bands at MW 105 and 50?”

The original Figure 5B is now revised Figure 2B. Please note that quantification (relative densi-tometry of RIPK3) is provided below the RIPK3 blot. For the NF�B1 blot, the antibody used rec-ognizes both subunits of the protein (p105 and p50), which are shown on the blot at their corre-sponding molecular weights. We have now added arrows to clarify that those are the bands of in-terest (the band located between 105 and 50 kDa is a background band picked up by the anti-body).

Reviewer #3

1. (Major) “What is the resolution of GLoPro? Would you anticipate that all three probes would iden-tify the same interacting proteins? For the MS1 NF�B1 ChIP data, it seems to only interact with a distal region (-1 kb), but the GLoPro showed interaction with all three probes, which were more proximal to the promoter. Is this due to differences in resolution between these two techniques?”

Myers et al reported that the GLoPro technique biotinylates proteins within 400bp of a genomic target [13]. Therefore, given that our sgRNAs spanned a region of 300 bp (-261 through +39 of the Ripk3 promoter), we do predict that they would identify a largely overlapping set of interacting proteins. Our original ChIP for NF�B1 binding in MS1 cells showed the protein sitting ~1 kb up-stream (-1.0 kb) of the Ripk3 transcription start site under basal conditions (original Figure 4A, also shown in Figure R1D below). For this revision we performed more extensive ChIP analysis of HUVECs and found NF�B1 and IKBKG sitting ~0.5 kb upstream of the TSS under basal condi-tions (p=0.14 and 0.03, respectively; see revised Figure 4A). Because the majority of our soni-cation fragments for ChIP are ~250-750 bp in size, we believe our ChIP and GLoPro data are consistent with each other in terms of indicating that NF�B1 and IKBKG can bind within 1 kb of the Ripk3 TSS in endothelial cells.

2. (Major) “Are there cis elements in the RIPK3 promoter that match the transcription factors that were identified? This is especially relevant for NF�B1. Where are the NF-�B elements and is the binding predicted to be conserved across species? Does mutation of NF-�B motifs affect pro-moter activity in a luciferase assay?”

We used the Meme Suite (https://meme-suite.org/meme/) to analyze the murine Ripk3 promoter for predicted NF-�B transcription factor binding sites. The position weight matrix shown below in Figure R1 demonstrates an NF-�B consensus binding motif located between -1258 bp and -1237 bp within the Ripk3 promoter. This binding motif is based on the described consensus DNA se-quence of 5’-GGGRNYYYCC-3’ (in which R is a purine, Y is a pyrimidine, and N is any nucleo-tide) that has been reported for NF-�B transcription factors [14]. Although the Meme Suite did not predict a comparable NF-�B binding site in the human Ripk3 promoter, our lab has shown that there is high sequence conservation of the Ripk3 promoter around the -1.0 kb and -0.2 kb re-gions across species [6]. This conservation guided our analysis of these regions in our ChIP ex-periments. Please note that because we could not pinpoint specific NF�B1 or IKBKG binding se-quences in the human Ripk3 promoter, we could not perform the relevant luciferase assays suggested above in HUVECs.

3. (Major) “It would be helpful if there was additional validation of the GLoPro technique beyond just NF�B1.”

Please see our response to Reviewer 2, question #4.

4. (Major) “Does NF�B1 knock-down in MS1 cells affect RIPK3 expression?”

We used the immortalized MS1 endothelial cell line to perform GLoPro because this assay re-quires clonal selection and a large number of cells (~4X108), which are impractical hurdles when using primary endothelial cells like HUVECs. When we obtained our GLoPro results, we initially began validating them in the MS1 line. Indeed, we did see a small but significant decrease in Ripk3 transcripts when we knocked down NF�B1 (see Figure R2A below). We likewise saw a small but significant decrease in luciferase activity when we knocked down NF�B1 in MS1 cells transfected with a luciferase reporter driven by a portion of the Ripk3 promoter to which we can ChIP NF�B1 (see Figure R2B,D below). Finally, we saw a small but significant increase in Ripk3 transcripts when we overexpressed NF�B1 in MS1 cells (see Figure R2C below). Together these data indicate that NF�B1 manipulation can impact Ripk3 transcription in MS1 cells, but be-cause this is an immortalized cell line, we thought it would be important to validate the ability of NF�B1 to influence Ripk3 transcription in primary endothelial cells such as HUVECs (see re-sponse to Reviewer #1, question #5). Our HUVEC data do validate NF�B1 as a transcriptional regulator of Ripk3, but they reveal a different regulatory relationship from what we saw in MS1 cells: NF�B1 represses Ripk3 transcription when HUVECs are challenged with TNF�—a major stimulus for NF-�B signaling. We believe the large and highly significant effects we see on Ripk3 transcription and on RIPK3-mediated cell death in HUVECs following NF�B1 knockdown and TNF� stimulation are more compelling than the nominal changes we saw in baseline MS1 cells with NF�B1 manipulation.

In summary, we acknowledge the different effects on Ripk3 transcription when we knockdown NF�B1 in MS1 cells (small reduction) versus HUVECs (big increase when cells are stimulated with TNF�). We also acknowledge that baseline RIPK3 protein is much more highly expressed in the two immortalized endothelial cell lines we analyzed (MS1 and C166) than in HUVECs (original Figure S1). We don’t know the reason for this expression difference, but we suspect the high levels of RIPK3 in MS1 cells made it beneficial for using GLoPro to identify proteins that sit at the Ripk3 promoter and impact its transcription. Nevertheless, we maintain that functional validation of the true regulatory roles of our GLoPro-identified proteins is best reserved for primary endo-thelial cells like HUVECs with more physiological RIPK3 expression.*

*We have only seen substantial in vivo endothelial RIPK3 expression in mouse embryos dur-ing stages of active angiogenesis [1, 6, 7].

5. (Minor) “It isn’t clear how the control probe was designed.”

The control probe for the GLoPro analysis (non-targeting gRNA; NT-gRNA) was designed so as not to recognize any sequence in the mouse genome, as described [15].

6. (Minor) “Are the GO terms shown in the figures complete or selected GO terms? This should be indicated in the figure legends.”

The GO terms associated with the GLoPro heat map (original Figure 2; revised Figure S2A) were filtered to include terms that include “nuclear as cellular component” and “transcription as molecular function,” since our goal was to identify transcriptional regulators of Ripk3. The GO terms shown in the original Figure 3 (revised Figure S2A) are further (unfiltered) functional anno-tations of the 41 “nuclear” proteins identified in Figure 2. These distinctions are explained in the legend for Figure S2.

7. (Minor) “Information on the number of replicates that were performed should be included in the figure legends.”

This information is now included in the figure legends.

8. (Minor) “In Figure 2, it would be helpful to show the data from the control oligo in the heat map for comparison purposes.”

We have modified the heat map (now shown in revised Figure 1C) to accommodate this sugges-tion.

In summary, we have made the following additions and changes to this manuscript in response to the Reviewers’ suggestions:

• Combined original Figures 1 and 2

• Moved original Figure 3 to the supplement (now Figure S2)

• Generated new analysis of an additional GLoPro target protein and NF-�B signaling pathway component: IKBKG. We showed by immunostaining that IKBKG has significant nuclear locali-zation in HUVECs grown under basal conditions or with TNF� stimulation (new Figure 3A). We also showed knockdown of IKBKG in HUVECs stimulated with TNF� significantly ele-vates Ripk3 transcripts (new Figure 3B)*.

*Please note that while analyzing Ripk3 transcription following IKBKG knockdown, we also repeated NF�B1 knockdown in the same experimental runs (both as a control and as fur-ther validation of the NF�B1 effects on Ripk3 transcription from a different author). Our revised Figure 2A now includes our most current analyses of NF�B1 knockdown effects on Ripk3 transcription. Note, the data from non-specific-siRNA-treated cells are identical for Figure 2A and 3B, since the analyses were performed at the same time (this is indicat-ed in our new figure legend for Figure 3). Therefore, the effects of NF�B1 and IKBKG knockdown can be directly compared because they were generated in the same experi-ments, but we separated out the data into Figures 2A and 3B so that we could present the NF�B1 and IKBKG stories sequentially and logically.

• Generated all new ChIP-qPCR analysis of NF�B1 and IKBKG binding to the Ripk3 promoter in HUVECs, both at basal conditions and after TNF� treatment (revised Figure 4). ChIP ex-periments were performed three separate times so that appropriate quantification and statis-tical analyses of the findings could be presented, as requested.

• Manuscript text was modified to include the new IKBKG data and to incorporate Reviewer suggestions.

Thank you for considering these revisions; we believe they shed additional novel insights into endo-thelial Ripk3 transcriptional regulation, particularly under inflammatory stimulation.

Sincerely,

Courtney Griffin, Ph.D.

References for Rebuttal Letter

1. Gao S, Griffin CT. RIPK3 modulates growth factor receptor expression in endothelial cells to support angiogenesis. Angiogenesis. 2021. Epub 2021/01/16. doi: 10.1007/s10456-020-09763-5. PubMed PMID: 33449298.

2. Jacobsen MD, Weil M, Raff MC. Role of Ced-3/ICE-family proteases in staurosporine-induced programmed cell death. J Cell Biol. 1996;133(5):1041-51. Epub 1996/06/01. doi: 10.1083/jcb.133.5.1041. PubMed PMID: 8655577; PubMed Central PMCID: PMCPMC2120856.

3. Galluzzi L, Kepp O, Kroemer G. RIP kinases initiate programmed necrosis. J Mol Cell Biol. 2009;1(1):8-10. Epub 2009/08/15. doi: 10.1093/jmcb/mjp007. PubMed PMID: 19679643.

4. Narayan N, Lee IH, Borenstein R, Sun J, Wong R, Tong G, et al. The NAD-dependent deacetylase SIRT2 is required for programmed necrosis. Nature. 2012;492(7428):199-204. Epub 2012/12/04. doi: 10.1038/nature11700. PubMed PMID: 23201684.

5. Degterev A, Zhou W, Maki JL, Yuan J. Assays for necroptosis and activity of RIP kinases. Methods Enzymol. 2014;545:1-33. doi: 10.1016/B978-0-12-801430-1.00001-9. PubMed PMID: 25065884.

6. Colijn S, Gao S, Ingram KG, Menendez M, Muthukumar V, Silasi-Mansat R, et al. The NuRD chromatin-remodeling complex enzyme CHD4 prevents hypoxia-induced endothelial Ripk3 transcription and murine embryonic vascular rupture. Cell Death Differ. 2020;27(2):618-31. Epub 2019/06/27. doi: 10.1038/s41418-019-0376-8. PubMed PMID: 31235857.

7. Colijn S, Muthukumar V, Xie J, Gao S, Griffin CT. Cell-specific and athero-protective roles for RIPK3 in a murine model of atherosclerosis. Dis Model Mech. 2020;13(1). Epub 2020/01/19. doi: 10.1242/dmm.041962. PubMed PMID: 31953345; PubMed Central PMCID: PMCPMC6994951.

8. Lacorre DA, Baekkevold ES, Garrido I, Brandtzaeg P, Haraldsen G, Amalric F, et al. Plasticity of endothelial cells: rapid dedifferentiation of freshly isolated high endothelial venule endothelial cells outside the lymphoid tissue microenvironment. Blood. 2004;103(11):4164-72. Epub 2004/02/21. doi: 10.1182/blood-2003-10-3537. PubMed PMID: 14976058.

9. Xia P, Gamble JR, Rye KA, Wang L, Hii CS, Cockerill P, et al. Tumor necrosis factor-alpha induces adhesion molecule expression through the sphingosine kinase pathway. Proc Natl Acad Sci U S A. 1998;95(24):14196-201. Epub 1998/11/25. doi: 10.1073/pnas.95.24.14196. PubMed PMID: 9826677; PubMed Central PMCID: PMCPMC24350.

10. Israel A. The IKK complex, a central regulator of NF-kappaB activation. Cold Spring Harb Perspect Biol. 2010;2(3):a000158. Epub 2010/03/20. doi: 10.1101/cshperspect.a000158. PubMed PMID: 20300203; PubMed Central PMCID: PMCPMC2829958.

11. Legarda-Addison D, Hase H, O'Donnell MA, Ting AT. NEMO/IKKgamma regulates an early NF-kappaB-independent cell-death checkpoint during TNF signaling. Cell Death Differ. 2009;16(9):1279-88. Epub 2009/04/18. doi: 10.1038/cdd.2009.41. PubMed PMID: 19373245; PubMed Central PMCID: PMCPMC2728158.

12. Hwang B, McCool K, Wan J, Wuerzberger-Davis SM, Young EW, Choi EY, et al. IPO3-mediated Nonclassical Nuclear Import of NF-kappaB Essential Modulator (NEMO) Drives DNA Damage-dependent NF-kappaB Activation. J Biol Chem. 2015;290(29):17967-84. Epub 2015/06/11. doi: 10.1074/jbc.M115.645960. PubMed PMID: 26060253; PubMed Central PMCID: PMCPMC4505044.

13. Myers SA, Wright J, Peckner R, Kalish BT, Zhang F, Carr SA. Discovery of proteins associated with a predefined genomic locus via dCas9-APEX-mediated proximity labeling. Nat Methods. 2018;15(6):437-9. Epub 2018/05/08. doi: 10.1038/s41592-018-0007-1. PubMed PMID: 29735997; PubMed Central PMCID: PMCPMC6202184.

14. Wan F, Lenardo MJ. Specification of DNA binding activity of NF-kappaB proteins. Cold Spring Harb Perspect Biol. 2009;1(4):a000067. Epub 2010/01/13. doi: 10.1101/cshperspect.a000067. PubMed PMID: 20066093; PubMed Central PMCID: PMCPMC2773628.

15. Doench JG, Fusi N, Sullender M, Hegde M, Vaimberg EW, Donovan KF, et al. Optimized sgRNA design to maximize activity and minimize off-target effects of CRISPR-Cas9. Nat Biotechnol. 2016;34(2):184-91. Epub 2016/01/19. doi: 10.1038/nbt.3437. PubMed PMID: 26780180; PubMed Central PMCID: PMCPMC4744125.

Submitted filename: Response to Reviewers PONE-D-2-35540.docx

Click here for additional data file.

25 May 2021

PONE-D-20-35540R1

Genomic locus proteomic screening identifies the NF-kB signaling pathway components NFkB1 and IKBKG as transcriptional regulators of Ripk3 in endothelial cells

PLOS ONE

Dear Dr. Griffin,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

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Ramani Ramchandran

Academic Editor

PLOS ONE

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Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice.

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Reviewers' comments:

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Comments to the Author

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Reviewer #1: All comments have been addressed

Reviewer #2: All comments have been addressed

Reviewer #3: All comments have been addressed

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Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

**********

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Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

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Reviewer #1: Yes

Reviewer #2: (No Response)

Reviewer #3: Yes

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Reviewer #1: I thank the authors for addressing all the comments and making the manuscript more commendable. I would also recommend studying RIPK3 in other primary endothelial cells where RIPK3 is expressing in high levels.

Reviewer #2: Authors have incorporated all suggestions raised for Results, Figures, and Method Sections, which have improved flow and clarity of the manuscript. In addition, author have validated another IKBKG protein which is important for NF-B pathway and discussed their results nicely.

Minor comments: Although, authors have added statistical analysis information in the figures as well as legends, but it appears vague. Is their any rational to use two different statistics tests for example?

• Figure2: Error bars represent S.D. All 420 statistics were calculated using a one-sample t and Wilcoxon test. (*) indicates 421 statistical significance (p<0.05).

• Figure3: All quantified data are presented as mean � S.D. 421 All statistics were calculated using a two-way ANOVA with a Tukey’s multiple 422 comparisons test. (*) indicates statistical significance (p<0.05)

Author should add detail statistical analysis methods information for each panel & how they were compared in ‘Statistics’ section.

Reviewer #3: The authors have responded to the previous reviews and the manuscript is now acceptable. I have no other comments.

**********

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Reviewer #1: Yes: KARTHIKEYAN THIRUGNANAM

Reviewer #2: No

Reviewer #3: No

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2 Jun 2021

Please see the attached formatted "Response to Reviewers" letter, which contains the following content:

May 30, 2021

Ramani Ramchandran

Academic Editor

PLOS ONE

RE: Resubmission of PONE-D-20-35540R1

Dear Dr. Ramchandran:

Thank you for the recent reviews of our revised manuscript “Genomic locus proteomic screening identifies the NF-�B signaling pathway components NF�B1 and IKBKG as transcriptional regulators of Ripk3 in endothelial cells.” Reviewer #2 requested a more thorough description of our statistical methods; we appreciated this suggestion and have included responses below:

Reviewer #2:

Minor comments: Although, authors have added statistical analysis information in the figures as well as legends, but it appears vague. Is there any rational to use two different statistics tests for example?

Figure 2: Error bars represent S.D. All statistics were calculated using a one-sample t and Wilcoxon test. (*) indicates statistical significance (p<0.05).

We chose to use a one-sample t and Wilcoxon test to determine if the mean of ChIP enrichment (for NF�B1 or for IKBKG) is statistically different from the normalized negative IgG control. This test was chosen because we were comparing one variable: each mean enrichment value (independently) against the calculated IgG control enrichment levels.

Figure 3: All quantified data are presented as mean S.D. all statistics were calculated using a two-way ANOVA with a Tukey’s multiple comparisons test. (*) indicates statistical significance (p<0.05).

We chose to use a two-way ANOVA with a Tukey post hoc test because we were comparing two factors simultaneously: siRNAs (nonspecific or gene-specific) and treatment (vehicle or TNF� or Z-VAD-FMK or NSA).

Author should add detail statistical analysis methods information for each panel and how they were compared in “Statistics” section.

We have updated the “Statistics” section within the “Materials and methods” to say the following (new lines 259-268):

Results are presented as mean � S.D. of n independent experiments (n is reported in the figure legends). Data normality was determined using the D'Agostino-Pearson omnibus test. Two-way ANOVA with a Tukey post hoc test was used to determine changes in HUVECs knocked down with nonspecific siRNA or gene of interest-specific siRNA after treatment with vehicle or TNF� or Z-VAD-FMK or NSA (Figs 2A, 2C, 2D, 3B). One-sample t and Wilcoxon test was used to determine fold-change of ChIP enrichment compared to the normalized negative IgG control (Figs 4A and 4B). Significance was determined by a P-value of 0.05 or less. All statistical analyses were achieved using GraphPad Prism8 software.

Thank you for this opportunity to improve the statistical descriptions associated with this revised manuscript.

Sincerely,

Courtney Griffin, Ph.D.

Submitted filename: Response to Reviewers PONE-D-2-35540R1.docx

Click here for additional data file.

8 Jun 2021

Genomic locus proteomic screening identifies the NF-kB signaling pathway components NFkB1 and IKBKG as transcriptional regulators of Ripk3 in endothelial cells

PONE-D-20-35540R2

Dear Dr. Griffin,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements. In the proofs, please include the details of the rationale for the statistical tests as you provided in the response to reviewer 2 comments. This will help in understanding the choice of statistical test.

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Kind regards,

Ramani Ramchandran

Academic Editor

PLOS ONE

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Reviewers' comments:

10 Jun 2021

PONE-D-20-35540R2

Genomic locus proteomic screening identifies the NF-kB signaling pathway components NFκB1 and IKBKG as transcriptional regulators of Ripk3 in endothelial cells

Dear Dr. Griffin:

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PLOS ONE