Identification of a lipid oxygen radical defense pathway and its epigenetic control

Domain: neuroscience
Published: 2025-12-11
Editorial outcome: major_revision

Abstract
Membrane phospholipids are vulnerable to oxidative radicals, and uncontrolled lipid peroxidation affects cell viability. Cells have evolved quality control and defense mechanisms, of which the genetic regulation is not fully understood. Here, we identify what we have coined the Lipid Oxygen Radical Defense (LORD) pathway. It is epigenetically repressed by a complex comprising the KRAB-zinc finger protein ZNF354A, the scaffold protein KAP1/TRIM28, the histone methyltransferase SETDB1, and the transcriptional activator ATF2. Upon lipid peroxide accumulation, p38- and JNK-dependent phosphorylation of ATF2, KAP1/TRIM28, and ZNF354A lead to disassembly of the repressive complex, releasing ZNF354A from specific DNA loci and activating a network of protective genes, including NRF2 targets. The pathway affects the cellular sensitivity to oxidative stress and ferroptosis, revealing a previously uncharacterized layer of epigenetic control in lipid quality control and damage repair. This positions the LORD pathway as a promising therapeutic target for diseases linked to chronic inflammation, neurodegeneration and cancer.

Introduction
Reactive oxygen species (ROS) are inevitable byproducts of aerobic metabolism1,2. These molecules play a dual role in cellular physiology: they are vital for signaling pathways1,2, but excessive ROS accumulation leads to oxidative stress and cellular damage1–3. Elevated hydrogen peroxide (H₂O₂) levels can trigger Fenton reactions with transition metals, such as ferrous iron (Fe²⁺), producing highly reactive hydroxyl radicals that inflict severe oxidative damage to biomolecules such as DNA, proteins, and lipids1,2, particularly phospholipids containing polyunsaturated fatty acids (PUFAs) present in cellular membranes4–6. Accumulation of lipid peroxides and their deleterious by-products is a hallmark of oxytosis or ferroptosis, a non-apoptotic form of cell death increasingly recognized for its importance in aging, cancer, cardiovascular disease, neurodegeneration, and chronic inflammation4,5,7–11.

Cells have evolved sophisticated antioxidant defense systems to protect against membrane lipid peroxidation, both selenium/thiol-dependent and independent pathways7,9,12,13. How these quality control mechanisms are regulated at a transcriptional level, particularly in complex organisms like mammals14, is not fully understood, and is the focus of the present study.

A complex network of transcription factors coordinates oxidative stress responses, with NRF2 (NF-E2-related factor 2) as the principal regulator2,9,14–16. Controlled by the redox-sensitive cytoplasmic inhibitor Keap1, NRF2 binds to antioxidant response elements (ARE) in the 5′ UTR, driving the expression of antioxidant genes, xenobiotic transporters, and iron homeostasis regulators15–18. NRF2 controls various detoxification systems7,15,17,19, including the thiol-independent oxidoreductase FSP1 (ferroptosis suppressor 1)20–22 and factors required for glutathione (GSH) synthesis, such as SLC7A11, the cystine/glutamate antiporter crucial for cystine uptake23,24. GSH is essential for the activity of GPX4 (glutathione peroxidase-4), the primary enzyme that reduces lipid hydroperoxides13,25. GPX4 is regulated by NRF1, highlighting functional overlap among transcription factors while maintaining distinct cellular targets26. Other factors like NF-κB, HIF-1, FOXO1, p53, YAP/TAZ, and ATF4 are also involved in maintaining redox balance, influencing lipid peroxidation, inflammation, and hypoxia responses, ultimately affecting cellular sensitivity to oxidative stress2,14,27–31. Redox-driven epigenetic modifications can further shape the expression of specific antioxidant genes32–34. However, despite this wealth of information, major gaps in understanding the transcriptional regulation of lipid quality control remain. The existence of a master regulator remains uncertain, and the mechanisms controlling specific antioxidant gene programs are yet to be elucidated.

In this study, we uncovered a defense pathway against ROS-triggered lipid damage, which we have termed the LORD pathway, for Lipid Oxygen Radical Defense. This pathway is under epigenetic regulation. DNA recognition is mediated by ZNF354A, a member of the largest family of mammalian transcriptional modulators, the Krüppel-associated box (KRAB) domain zinc finger proteins (KZFP)35,36. We found that ZNF354A is part of a repressive complex containing the global repressor KAP1/TRIM28 (hereafter referred to as KAP1), the histone methyltransferase SETDB1, but also the transcriptional activator ATF2, which plays a crucial regulatory role. Under homeostatic conditions, the ZNF354A-containing complex represses transcriptional programs involved in lipid quality control, antioxidant defenses, and other response pathways. Accumulation of lipid peroxides leads to phosphorylation-dependent disassembly of the repressive complex, and release of ZNF354A from specific DNA loci, allowing activation of the antioxidant response pathway. This work highlights the under-explored dynamics of epigenetic repressive complexes and the genetic response to oxidative lipid damage. It also paves the way towards the identification of potential targets for therapeutic intervention in a variety of conditions such as chronic inflammation, infections, cancer, and aging-related disorders.

Results
ZDHHC20L as a readout for the stress response pathway
In previous work on the S-acylation of the SARS-CoV-2 Spike protein by the acyltransferase ZDHHC2037,38, we found that infection induces a transcriptional shift in the ZDHHC20 gene, generating N-terminally extended isoforms of the protein, which we here collectively term ZDHHC20 Long (ZDHHC20L). These longer isoforms are also expressed in cells exposed to the pore-forming toxin aerolysin and in vivo, upon chemical-induced colitis37. We additionally documented the presence of ZDHHC20L in untreated hepatocellular carcinoma cell line HepG237, a finding we extended here to MCF7 breast cancer and HCT116 human colorectal carcinoma cells (Fig. 1a). We also investigated whether ZDHHC20L expression could be induced by aging, a process where increased stress pathways are linked to the gradual decline of repair mechanisms39. While in total cell extracts (TCEs) from primary lung epithelial cells of young donors only the canonical form of ZDHHC20 was detected, ZDHHC20L became increasingly expressed in cells from donors above 60 (Fig. 1b). ZDHHC20L expression is thus induced under a variety of conditions, ranging from some cancers to aging, viral infection, and other stresses. This study aimed to identify the stress response pathway that leads to ZDHHC20L expression.

Activation of the transcription factor ATF2 triggers ZDHHC20L expression
To elucidate the molecular mechanisms underlying ZDHHC20L expression, we mined experimental gene occupancy data from ENCODE-3 (Encyclopedia of DNA Elements)40,41 hosted in the UCSC Genome Browser (Transcription Factor ChIP-seq Clusters)42. We previously found that ZDHHC20L is translated from upstream in-frame AUGs, generating longer transcripts. We also showed that FOXA1 and SP1 are transcription regulators, which bind ~5 kb upstream of the in-frame start codons, in HepG2, human liver cancer, cells37. Here, we found that the stress-regulated transcriptional activator ATF243 was recruited ~5 kB further upstream (Fig. 1c) and evaluated its role in ZDHHC20L expression. In Hela cells, where ZDHHC20L can be induced by aerolysin37, we found that siRNA-silencing of ATF2 (Supplementary Fig. 1a) significantly reduced the toxin-induced ZDHHC20L expression (Fig. 1d).

Different kinases activate ATF2 in response to stress or growth signals44–50 and aerolysin treatment also led to ATF2 (both endogenous and over-expressed) phosphorylation, on Thr-69, within its transactivation region46 (Fig. 1d, Supplementary Fig. 1b). The presence of multiple phospho-bands at around >55 kDa suggests phosphorylation on several residues and/or of various ATF2 isoforms51. ATF2 phosphorylation could be detected under all tested conditions leading to ZDHHC20L expression: in primary lung epithelial cells from older donors or subjected to SARS-CoV-2 infection (Supplementary Fig. 1c), in the duodenum of mice (where ZDHHC20L is constitutively expressed37-Supplementary Fig. 1d), and in the colon of mice upon chemical-induced colitis (Supplementary Fig. 1e). Thus, ATF2 phosphorylation is consistently associated with ZDHHC20L expression.

To assess the importance of ATF2 phosphorylation in regulating ZDHHC20L expression, we generated ATF2 phospho-site mutants, either mimicking phosphorylation by aspartic acid substitution or preventing it by alanine substitution, targeting four residues in the N-terminal activation domain Thr-52, 69, 71 and 7350 (to D or A-coined 4D and 4A), two in the C-terminal regulatory domain Ser-490 and 49844 (2D and 2A), or all six combined (6D and 6A). Using bone-derived U2OS cells, which only express the canonical form of ZDHHC20, overexpression of any of the ATF2 phospho-mimetic mutants was sufficient to induce ZDHHC20L expression, in the absence of any stimulus (Fig. 1e, and Supplementary Fig. 1f). This process still required FOXA1 and SP1, as it was blocked by the combined depletion or pharmacological inhibition of these transcription factors with JQ1 and mithramycin respectively (Supplementary Fig. 1g). Consistently, wild-type ATF2, but not ATF2-6A, when co-expressed with FOXA1 and SP1, also led to ZDHHC20L expression (Fig. 1e), which did not occur when only two of these factors were over-expressed (Supplementary Fig. 1h). To explore an additional functional outcome beyond controlling expression of ZDHHC20L during stress, we investigated whether ATF2 activation is protective against exposure to aerolysin, which like other pore-forming toxins disrupts plasma membrane integrity that can lead to cell death through various pathways52,53. Silencing ATF2 increased cell sensitivity to aerolysin (Fig. 1f), which was rescued by expressing wild type (WT) or the phosphomimetic 6D ATF2 but not the 6A mutant (Fig. 1f). Thus, activated ATF2 drives ZDHHC20L expression and has a protective effect towards aerolysin-induce cell death.

ZDHHC20L is repressed by a heterochromatin-inducing complex
We further analyzed ENCODE ChIP-seq data and identified reported binding sites for the protein scaffold KAP1 (KRAB domain-associated protein 1) and the histone methyltransferase SETDB1 (SET Domain Bifurcated Histone Lysine Methyltransferase 1), near the ATF2 binding regions in U2OS and K562 lymphoblast cells (Fig. 1c)54,55. These two proteins are part of a chromatin-modifying complex that mediates histone 3 lysine 9 trimethylation (H3K9m3), leading to the formation of heterochromatin54 and transcriptional repression54–57 (Fig. 1g, top panel). In U2OS cells, SETDB1 silencing (Supplementary Fig. 1a) alone induced ZDHHC20L expression (Fig. 1h), which was suppressed by wild-type SETDB1 but not by a catalytically inactive mutant (Fig. 1i), confirming the need for its enzymatic activity. KAP1 silencing (Supplementary Fig. 1a) or knockout in haploid HAP1 cells (Fig. 1j) similarly triggered ZDHHC20L expression (Fig. 1j) and the emergence of extended ZDHHC20 mRNA transcripts, as shown by qPCR (Fig. 1k)37. KAP1 and SETDB1 therefore repress ZDHHC20L expression, in contrast to ATF2 that is required for stress-induced ZDHHC20L expression.

Given the involvement of SETDB1 and KAP1, we analyzed ENCODE ChIP-seq data to assess whether histone modifications had been reported at the ZDHHC20 locus. In U2OS cells, repressive H3K9me3 marks were detected around the SETDB1, KAP1, and ATF2 peaks (Fig. 1c). Additional H3K9me3 marks within the first intron overlapped a second SETDB1 peak, potentially reinforcing ZDHHC20L silencing. Active promoter marks H3K27Ac and H3K4me3 (Fig. 1g, lower panel) were found flanking these repressive regions and co-localizing with both the short-canonical and long ZDHHC20 transcription start sites (Fig. 1c). The enhancer mark H3K4me1 (Fig. 1g) aligned with FOXA1 and SP1 ChIP-seq peaks in HepG2 cells (Fig. 1c), which constitutively express ZDHHC20L even without stimulation37. Altogether, these data show that under homeostatic conditions the expression of ZDHHC20L isoforms is repressed by the heterochromatin-inducing KAP1/SETDB1 complex.

ZNF354A recruits the repressive complex to the ZDHHC20L regulatory region
KAP1/SETDB1 complexes are generally tethered to DNA by KRAB-containing zinc finger proteins (KZFPs) (Fig. 1g), of which ~380 are encoded by the human genome54,55,57. To identify the KZFP responsible for docking KAP1 at the ZDHHC20 locus, we mined KRABopedia, a published ChIP-seq dataset generated from HEK293T cells overexpressing HA-tagged forms of each KZFP individually58,59. The binding sites of several KZFPs map to the promoter region of ZDHHC20 (Fig. 2a, Supplementary Fig. 2a), a pattern that is not uncommon for this class of proteins58,59. In contrast, ZNF317, ZNF354A, ZNF677, and ZNF793 have binding sites within the “repression” region of the acyltransferase gene. ZNF354A binding sites co-localize with the SETDB1 and H3K9me3 peaks upstream and downstream of the ZDHHC20 TSSs (Fig. 2a, and Supplementary Fig. 2a). We silenced each of the four KZFPs individually in U2OS cells using mixes of siRNAs (Supplementary Fig. 2b). Only the ZNF354A knockdown led to the expression of ZDHHC20L (Fig. 2b), which could be reverted by the expression of ZNF354A-HA (Supplementary Fig. 2c). Importantly, silence of ZNF354A did not lead to a decrease of the mRNA of its paralogue ZNF354B, with which it shares 86% identity (Supplementary Fig. 2de), and consistently ZNF354B silencing did not trigger ZDHHC20L expression (Supplementary Fig. 2f).

We next tested the specificity for ZNF354A versus other KZFPs by immunoprecipitation (IP) experiments. Upon IP of KAP1 from U2OS cells overexpressing ZNF354A or two irrelevant KZFPs, all three KZFPs co-precipitated with KAP1, as the presence of canonical KRAB domains would predict60. Interestingly, the interaction between KAP1 and ZNF354A was disrupted by aerolysin treatment, which was not the case for the two other KZFPs (Fig. 2c). Thus, under basal conditions, ZNF354A recruits the KAP1 repressive complex to the 5′ regulatory region of DNA loci such as the ZDHHC20 locus. This interaction is disrupted upon aerolysin treatment, leading to the dissociation of ZNF354A and KAP1.

Dynamics of the KAP1-ZNF354A containing repressive complex
Since ATF2, KAP1 and ZNF354A bind to the same region within the ZDHHC20 5’UTR, we tested whether they could be part of a single complex. We immunoprecipitated KAP1 from ZNF354A-FLAG-expressing cells, which were depleted or not of endogenous ATF2 using siRNA, and recomplemented with wild-type or ATF2 phosphorylation mutants (6A and 6D). Under resting conditions, KAP1 co-precipitated ZNF354A, as well as ATF2 (Fig. 2d). The co-precipitation between the three proteins was also observed when performing IPs against the ZNF354A HA tag (Supplementary Fig. 2g). Despite the disruption of the complex, ATF2 –especially its endogenous phosphorylated form– remained associated with KAP1 (Fig. 2d). These results indicate that a subset of ATF2-KAP1 interactions occurs independently of ZNF354A-mediated chromatin association. Since ATF2 has not previously been found to associate with KAP1-nucleated repressive complexes, we tested whether it also interacts with other KAP1–KZFP complexes. IP of ZNF317, ZNF677, and ZNF793 did not lead to the co-IP of ATF2 (Supplementary Fig. 2g, j). Thus, ATF2, KAP1 and ZNF354A are part of a somewhat non-canonical repressive complex. Interestingly, expression of the phospho-mimetic ATF2-6D mutant was sufficient to disrupt the KAP1–ZNF354A interaction even in the absence of aerolysin (Fig. 2d), indicating that ATF2 acts as an upstream, stress-sensitive regulator of the complex. The mechanisms underlying ATF2 recruitment to ZNF354A-specific KAP1 complexes remain to be elucidated.

Since ATF2 undergoes phosphorylation upon stress, we wondered whether the same occurs for KAP1 and ZNF354A. KAP1 is known to undergo phosphorylation on Ser-824 and Ser-473 in response to DNA damage61–65 and on Ser-473 under oxidative stress66. Using an anti-phospho-Ser-473-KAP1 antibody, we detected KAP1 Ser-473 phosphorylation during SARS-CoV-2 infection, concomitant with ATF2 activation (Fig. 2e). KAP1 Ser-473 phosphorylation was also observed upon aerolysin treatment (Supplementary Fig. 2h), detected in the duodenum of mice (Supplementary Fig. 1d), and in the colon of mice upon chemical-induced colitis (Supplementary Fig. 1e). To determine whether Ser-473 is the major phosphorylation site, we expressed WT KAP1 or the S473A phospho-deficient mutant in cells silenced for the endogenous protein and exposed them to aerolysin. Western blot analysis of KAP1 IP fractions, using anti-phospho-Ser/Thr antibodies, showed no signal for the S473A mutant (Fig. 2f), validating Ser-473 as the primary phosphorylation site under our conditions. Finally, we verified that Ser-473 phosphorylation was necessary to trigger ZDHHC20L expression upon aerolysin treatment (Supplementary Fig. 2i). As with ATF2, expression of a phospho-mimetic S473D KAP1 mutant was sufficient to trigger ZDHHC20L expression without any stimulus (Fig. 2g).

We next probed for the potential phosphorylation of ZNF354A. Aerolysin treatment and SARS-CoV-2 infection both induced serine/threonine phosphorylation of ZNF354A, detected by phospho-Ser/Thr antibodies in ZNF354A-IPs (Fig. 2h). This phosphorylated band corresponded to ZNF354A, as it was absent in ZNF354A-silenced cells (Fig. 2h). Aerolysin did not induce the phosphorylation of a control KZFP, ZNF793 (Supplementary Fig. 2j). Finally, aerolysin-induced phosphorylation of KAP1 and ZNF354A depended on ATF2 phosphorylation, which alone was sufficient to drive all these events (Fig. 2i).

Together, these findings demonstrate that ZDHHC20L expression is repressed by a complex comprising ATF2, SETDB1, KAP1, and ZNF354A. Upon stress, ATF2 is phosphorylated, followed by phosphorylation of KAP1 and ZNF354A, leading to dissociation of the KAP1–ZNF354A complex and induction of ZDHHC20L expression (Fig. 2j).

p38 and JNK trigger phosphorylation of the repressive complex components
To further explore the regulatory mechanisms of the ATF2-KAP1-ZNF354A complex, we identified the ZNF354A phosphorylation sites. Three residues, located in the linker region between the KAP1-binding KRAB domain and the DNA-binding domains, were found by phosphoproteomics in breast cancer (Ser-169 and Thr-185)67, and a subgroup of large T-cell lymphoma (T154)68 (https://www.phosphosite.org). This linker region is the most diverse between ZNF354A and ZNF354B. We generated the phospho-mutants of the three ZNF354A sites and expressed them in ZNF354A-silenced U2OS cells. A phospho-Ser/Thr signal was observed upon aerolysin treatment of WT ZNF354A-, but not S169A ZNF354A-expressing cells (Fig. 3a). The signal was reduced, but not absent, when expressing the T154A or T185A mutants (Fig. 3a), indicating a leading phosphorylation event at Ser169, as confirmed using phospho-tag gels (Fig. 3b). Ser-169 is absent in ZNF354B (Supplementary Fig. 2d).

We next searched for the kinases involved in ZDHHC20L expression. We tested a panel of inhibitors targeting MAPKs (e.g. JNK, p38, and ERK) and ATMs since these are known to modify KAP1 and ATF2 following different stresses, including infection69,70. Inhibition of either p38 or JNK abolished the aerolysin-induced expression of ZDHHC20L and KAP1 phosphorylation, and reduced phosphorylation of ATF2. ATF2 phosphorylation was also sensitive to ERK inhibition (Fig. 3c). p38 and JNK inhibitors similarly affected KAP1 and ZNF354A phosphorylation and ZDHHC20L expression in cells expressing the ATF2 6D mutant, in the absence of stressor (Fig. 3de). Thus, phosphorylation of ATF2, KAP1 (on Ser-473) and ZNF354 (on Ser-169) occurs in a p38- and JNK-dependent manner and is required for the expression of ZDHHC20L.

ZNF354A determines the genetic specificity of the cellular response to oxidative stress
We next explored whether the de-repression by the ZNF354A-containing complex has a broader effect than just controlling ZDHHC20L expression and could be coupled with the activation of specific host stress response/repair pathways. To identify genes that reside in the vicinity of the 1,665 ZNF354A peaks, we analyzed our ChIP-seq data from HEK293T cells overexpressing HA-tagged ZNF354A35,58 using GREAT (Genomic Regions Enrichment Annotations) with a 300kb window from the TSS as the cut-off for gene association71. GREAT analysis mapped the ZNF354A peaks to the regulatory regions of 2,116 genes associated with a variety of ontologies (Fig. 4a). Among the enriched pathways, selenium metabolism stood out due to its connection to defense against ROS (Fig. 4a). Further manual curation of the gene list led to the identification of additional selenium-related genes (Supplementary Fig. 3a).

The identified redox-related genes included: MAT1A (methionine adenosyltransferase 1A), which synthesizes S-adenosylmethionine, a precursor for GSH biosynthesis72; SLC7A11, encoding the main subunit of the cystine/glutamate antiporter system x−, essential for GSH production from extracellular cystine73; and TXNRD1 (thioredoxin reductase-1 and its homolog TXNRD3), which can reduce cystine after its uptake by the x− system thereby contributing to GSH synthesis74. We also found 8 selenoprotein-encoding genes (Supplementary Fig. 3a). These proteins, of which the human proteome counts 25, contain a selenocysteine in their primary sequence which they use to reduce H₂O₂ and organic hydroperoxides12,75.

To test whether ZNF354A is indeed a regulator of antioxidant defense genes, we performed RNA-seq upon ZNF354A knockdown in U2OS (Supplementary Fig. 4a), which led to the identification of 1,223 significantly upregulated genes (fold change >2, p-adjusted 0.05) (Fig. 4b). Gene Set Enrichment Analysis (GSEA) indicated that these genes are involved in protective responses against external insults, including bacteria, viruses and chemical stresses, as well as antioxidant activity, lipid perturbations, and the NRF2 pathway (Fig. 4cd, and Supplementary Fig. 4b, Supplementary Table 1 and Supplementary Data 1), pointing in the same direction as the above ChIP-seq analysis of ZNF354A-overexpressing HEK293T cells (Supplementary Fig. 3a).

Because the NRF2 pathway has a well-established regulatory role in antioxidant responses and has been reported to be positively regulated by KAP176, we tested its potential involvement in ZDHHC20L expression. While silencing ZNF354A leads to ZDHHC20L expression, this was prevented by the additional silencing of NRF2 (Supplementary Fig. 4cd). Thus, together with SP1 and FOXA137, NRF2 also positively regulates ZDHHC20L expression.

To validate the gene set of Supplementary Fig. 3a, we performed quantitative PCR (qPCR). In ZNF354A-silenced cells, the mRNA levels of MAT1A, SLC7A11, TXNRD1, the redox regulator GLRX (Glutaredoxin-1), SEPHS2 (selenophosphate synthetase) and FSP1 were all increased (Supplementary Fig. 4e), consistent with elevated protein levels of MAT1A (Supplementary Fig. 4a). Complementary qPCR analysis in cells overexpressing ZNF354A for 24h revealed downregulation of most of these target genes (Supplementary Fig. 4f), further supporting the regulatory role of ZNF354A.

As predicted by the analysis of the ZNF354A DNA binding regions (Fig. 4a), this KZFP is involved in the repression of genes encoding key antioxidant cellular defense effectors (Fig. 4, and Supplementary Fig. 4e, 4b, and Supplementary Table 1, Supplementary Data 1). Many of its target genes are indeed involved in GSH biosynthesis, iron metabolism, the mevalonate pathway, and the NADPH-FSP1-CoQ10 oxidoreductase system, which protects cells from lipid radical-induced damage21,22 (Fig. 4e). These various independent analyses point towards ZNF354A as a key regulator of the genetic control of cellular antioxidant defenses, both selenium/thiol-dependent and -independent, and thereby the cellular sensitivity to ferroptosis7,12,77.

To assess the evolutionary conservation of the pathway, we extended our analysis to the mouse ortholog of ZNF354A, ZFP354A. Using a liftover strategy42,78, we mapped human ZNF354A binding sites to the mouse genome assembly, identifying ~300 loci successfully converted. Remarkably, ZFP354A also binds near genes involved in antioxidant defense (Supplementary Fig. 3a). Consistently, silencing ZFP354A in mouse cells resulted in the expression of mouse ZDHHC20L (Supplementary Fig. 3b), mirroring our findings in human cells and supporting a conserved function of ZNF354A/ ZFP354A in regulating oxidative stress responses.

ZNF354A binds predominantly to transposable elements (TEs), with some additional binding observed in introns, as documented in Krabopedia58 (Supplementary Fig. 3c). Among enriched TE families, ZNF354A displays a strong preference for LINE-1 (Long Interspersed Nuclear Elements)15,19. In the curated, redox-associated gene signature upregulated upon ZNF354A depletion, the nearest ZNF354A peaks were also largely associated with LINE-1 elements (Supplementary data 1). Future research will investigate how the emergence of ZNF354A and its cognate TE targets contributed to shaping the regulatory network governing the LORD pathway in placental mammals. This includes examining the role of ZNF354B, which, despite its strong similarity to ZNF354A, exhibits a distinct binding profile with significantly fewer peaks, suggesting functional divergence (Supplementary Fig. 3e).

ZDHHC20L expression is induced by lipid peroxidation
Since ZNF354A regulates genes involved in cellular responses to oxidation, we explored whether oxidative damage could be the common primary trigger of the ZDHHC20L expression observed following SARS-CoV-2 infection, pore-forming toxin treatment, colitis, and aging (Fig. 1). When oxidative stress was induced by treating U2OS cells for 4-8h with H₂O₂ at 50 µM, a significantly lower concentration than used to induce DNA damage14, ZDHHC20L was expressed in a dose-dependent manner (Fig. 5a).

We next tested whether ZDHHC20L expression could be specifically triggered by inducing the accumulation of membrane lipid peroxides. These form when oxygen radicals interact with PUFA-containing phospholipids5,13,79. Under physiological conditions, their accumulation is avoided by the action of GPX4, the primary enzyme that detoxifies lipid peroxides, by reducing them to lipid alcohols23. Treating cells with the covalent GPX4 inhibitor RSL3 (RAS-selective-lethal-3)25 induced ZDHHC20L expression in a dose-dependent manner (Fig. 5b). H₂O₂ and RSL3 treatment also triggered phosphorylation of ATF2 (Fig. 5b), KAP-1, and ZNF354A (Supplementary Fig. 5a). Silencing of GPX4 similarly led to ZDHHC20L expression (Fig. 5c). Finally, since GPX4 requires GSH for its reduction, a third way of impairing its activity is to block cystine uptake via SLC7A11 (system Xc-). Erastin, a system Xc⁻ inhibitor80, also induced ZDHHC20L expression in a dose-dependent manner (Supplementary Fig. 5b).

Upon induction of lipid peroxidation, detoxification can also be performed chemically using lipophilic peroxyl radical-trapping molecules such as Ferrostatin-1 (Fer-1)81. Ferrostatin-1 inhibited the H₂O₂-induced expression of ZDHHC20L in a dose-dependent manner (Fig. 5d). Importantly, ferrostatin also inhibited aerolysin-induced ATF2 and KAP1 phosphorylation, ZDHHC20L expression (Fig. 5e), and diminished aerolysin-induced cell death (Supplementary Fig. 5c). Altogether, these observations demonstrate that lipid peroxide accumulation induces ZDHHC20L expression, whereas inhibition of lipid peroxidation by Ferrostatin-1 prevents this induction.

We next verified whether H₂O₂ could recapitulate the events triggered by aerolysin exposure or SARS-CoV-2 infection. H₂O₂ treatment led to the phosphorylation of ATF2, KAP1 (on Ser-473), and ZNF354A (on Ser-169), in a ferrostatin-dependent manner (Supplementary Fig. 5a). H₂O₂-induced ZDHHC20L expression was prevented by the expression of the phospho-deficient KAP1 S473A and ZNF354A S169A mutants (Supplementary Fig. 5d-f). The H₂O₂-induced ATF2, KAP1 and ZNF354A phosphorylation and ZDHHC20L expression were p38- and JNK-dependent (Fig. 6ab). Inhibition of ERK reduced ATF2 phosphorylation moderately, diminished ZNF354A phosphorylation, but did not affect KAP1 phosphorylation or ZDHHC20L expression (Fig. 6ab). ATM inhibition mildly reduced phosphorylation of all three components and the expression of ZDHHC20L (Fig. 6ab). Finally, H₂O₂ treatment triggered the detachment of KAP1 from ZNF354A, while phosphorylated ATF2 interacted with KAP1 (Fig. 6c).

Altogether, these observations demonstrate that H₂O₂ recapitulates the observations made with aerolysin, and can trigger the expression of ZDHHC20L through the p38/JNK-dependent phosphorylation of ATF2, KAP1 (Ser-473) and ZNF354A (Ser-169), and the disassembly of the repressive complex.

Stress-induced release of ZNF354A from regulatory loci
Thus far, our data indicate that the repressive complex contains ATF2-SETDB1-KAP1-ZNF354A and that upon lipid peroxidation-induced phosphorylation, KAP1 detaches from ZNF354A. We next tested whether, under these conditions, ZNF354A is released from the DNA. We performed genome-wide profiling of ZNF354A binding upon its overexpression in K562 cells, treated or not with H₂O₂ for 4h (Supplementary Fig. 6ab). As a preamble, we examined the genomic recruitment of this ZNF354A in untreated cells, and found it to be consistent with that previously recorded in 293T cells, with 20% of K562 peaks (306/1558) already identified in this other cell line (Supplementary Fig. 6c), representing a significant overlap compared to randomized regions (permutation test: 100 permutations, empirical P-value=0) (Fig. 6d). Additionally, the ZNF354A-HA signal intensity over peaks was highly consistent between the ChIP-seq experiments in the two cell lines (Fig. 6d). H₂O₂ treatment induced a severe drop in the number of ZNF354A-HA peaks (521 vs. 1558 peaks), and a significantly lower overlap with the peaks previously identified in HEK293T (6% vs. 20%, Fisher’s exact test, P-value=2.465e-16) (Fig. 6d). Moreover, ZNF354A occupancy was significantly reduced at the majority of identified peaks (Fig. 6e, and Supplementary Fig. 6c). That ZNF354A detaches from the DNA sites upon H₂O₂ treatment was further confirmed by ChIP-RT-qPCR for specific peaks associated with selected redox target genes, including MAT1A, SELS, TXNRD1 and ZDHHC20 (Fig. 6f). Together, these findings demonstrate that H₂O₂ treatment leads to the chromatin eviction of ZNF354A, to allow expression of previously repressed genes, notably those involved in antioxidant response.

ZNF354A acts as a regulator of ferroptosis sensitivity
To test the functional relevance of ZNF354A in controlling an antioxidant gene program, we tested whether silencing ZNF354A expression would protect cells from lipid peroxidation-induced death. We monitored lipid peroxidation, using two different fluorescent probes –C11-BODIPY and LiperFluo, the latter specifically detecting oxidized phospholipids82,83. Silencing ZNF354A expression led to a decrease in lipid peroxide levels (Fig. 7ab). ZNF354A-depleted cells also showed a moderate reduction in lipid peroxide accumulation following GPX4 inhibition with RSL3 compared to controls (Fig. 7ab). This suggests that in the absence of ZNF354A, cells have an increased ability to prevent the formation or detoxify lipid peroxides. Consistently, staining with the membrane-impermeant dye propidium iodide (PI) indicated that plasma membrane integrity was more preserved in ZNF354A-depleted cells than in control cells (Fig. 7c). Finally, cell viability was monitored by measuring ATP levels, following RSL3 or H₂O₂ treatment. Depletion of ZNF354A by siRNA led to a marked increase in viability in response to both RSL3 and H₂O₂ (Fig. 7d), as well as the cystine import inhibitors Erastin (Supplementary Fig. 7a).

These observations show that silencing ZNF354A expression reduces the cellular sensitivity to ferroptosis. We next tested whether ZNF354A overexpression would sensitize them. We designed inactive ZNF354A mutants by mutating the ZFP-KRAB-A box of ZNF354A, a well-conserved interaction domain of KZFP with KAP1 (Supplementary Fig. 7b)60, composed in particular of D18, E27, N45 and E4660,84,85. We generated a quadruple ZNF354A mutant construct with arginine substitutions of D18 and E27, or arginine and alanine substitutions of N45 and E46 (Supplementary Fig. 7b). While the mutant was expressed at WT levels, as predicted it failed to interact with KAP1 (Supplementary Fig. 7c). Overexpression of ZNF354A WT, but not ZNF354A Mut, led to an increase in oxidized phospholipids (Fig. 7e, and Supplementary Fig. 7d), associated with significant cell death starting at 48h (Fig. 7f). Cell viability could be rescued by ferrostatin-1, to levels that depended on the frequency of Fer-1 treatment (Fig. 7e, f, and Supplementary Fig. 7e-g). When ZNF354A was overexpressed to levels that led to 85% cell death after 4 days, daily administration of Fer-1 reduced death to 22 ± 16% (Supplementary Fig. 7g). Comparable protection was observed by treating cells with N-acetylcysteine amide (NAC), a cell-permeable cysteine derivative that restores GSH production, which reduced cell death to 12 ± 5% (Supplementary Fig. 7g). The treatment with both Fer-1 and NAC reduced cell death to 7 ± 1% (Supplementary Fig. 7g). Thus, cell death induced by ZNF354A overexpression is predominantly triggered by lipophilic ROS (≈75% contribution), with a minor contribution (<20%) by cytosolic or other ROS. Altogether, these observations show that ZNF354A silencing prevents excessive lipid peroxide accumulation and protects from cell death, while overexpression does the opposite.

As mentioned earlier, lipid peroxide detoxification relies mostly on GPX4 and FSP1, the latter operating in a GSH-independent manner via the NAD(P)H/FSP1/CoQ10 axis. We tested whether cell death induced by ZNF354A overexpression could be rescued by co-overexpression with either GPX4 or FSP1. FSP1 restored the viability of ZNF354A-overexpressing cells, consistent with the effect of Fer-1, while GPX4 did not (Fig. 7g). As this might reflect insufficient levels of GSH, we supplemented cells with NAC, which was sufficient to rescue ZNF354A-induced cell death, indicating that cellular GPX4 levels were not limiting (Fig. 7g). We then measured GSH levels to test whether they are influenced by ZNF354A. Silencing ZNF354A increased cellular GSH levels, as did to a greater extent silencing of GPX4 expression (Fig. 7h). Conversely, overexpression of ZNF354A led to a decrease in GSH (Fig. 7h). Thus, ZNF354A appears to act as a rheostat of cellular GSH levels.

The induction of ferroptosis is of major therapeutic interest to kill cancer cells25. To probe the relevance of the ZNF354A pathway in predicting and controlling the sensitivity of tumor cell lines to ferroptosis, we monitored the phosphorylation of ZNF354A. Only the cells expressing ZDHHC20L, i.e., HEPG2, MCF7, and HCT116 (Figs. 1a, 7i), showed phosphorylated ZNF354A, despite similar ZNF354A expression levels in all cells (Fig. 7i). We next submitted all cell lines to H₂O₂ or RSL3 treatment and monitored cell viability. Consistent with our hypothesis, HEPG2, MCF7, and HCT116 cells were more resistant to RSL3 and H₂O₂, compared to all other cancer lines (Fig. 7j).

Altogether, these findings indicate that ZNF354A regulates cellular GSH levels and lipid detoxification capacity, thereby modulating cellular sensitivity to lipid peroxidation-induced cell death pathways, in particular ferroptosis. In the context of cancer, the presence of phospho-ZNF354A or ZDHHC20L therefore appears predictive of tumor cell sensitivity to ferroptosis-inducing drugs.

ZDHHC20L is an effector of the ZNF354A-mediated pathway
In this study, we have so far used the expression of ZDHHC20L as a proxy to decipher the ZNF354A-mediated pathway. We initially identified ZDHHC20L in SARS-CoV-2-infected cells and could show that ZDHHC20L greatly outperforms the canonical enzyme in modifying the envelope glycoprotein Spike37,38. We postulated that the virus had hijacked a stress response pathway—presumably activated to fight infection—for its own benefit. Here, we hypothesized that ZDHHC20L may act as a bona fide effector of the ZNF354A-mediated pathway, with a role in redox homeostasis. To explore this possibility, we sought to identify potential redox-regulatory substrates of ZDHHC20L. Given the central role of GPX4 in detoxifying lipid peroxides and protecting against ferroptosis, we hypothesized that ZDHHC20L might regulate GPX4 through this modification. During the course of our study, two reports were published indicating that S-acylation of GPX4 is critical for its function in controlling cellular sensitivity to ferroptosis86,87. One study showed that GPX4 undergoes acylation by ZDHHC20 on Cys-6686, while the other proposed acylation by ZDHHC8 on Cys-7587. Our screen of the 23 human ZDHHC enzymes, initially tested in mixes of siRNA38, showed that only Mix3 led to a marked decrease in GPX4 3H-palmitate incorporation (Fig. 8ab). The enzymes targeted by Mix3, namely ZDHHC9, 14, 18, and 20, were subsequently tested individually. Only ZDHHC20 modified GPX4 in our cellular system (Fig. 8cd). We further confirmed S-acylation using a click chemistry-based approach, so-called ClickAcyl-PEG assay88, which involves labeling cells with a clickable palmitate analogue, and subsequently labeling the added acyl chains in vitro with azide-PEG to induce a band shift detected by SDS-PAGE and Western blotting. A clear GPX4 band shift towards two upper bands could be observed in control HEK293T cells, which was absent in the corresponding ZDHHC20 KO line (Fig. 8e). The double band shift is indicative of acylation on more than one cysteine, suggesting that both reported cysteines at positions 66 and 75 could be simultaneously subject to S-acylation86,87.

We next tested the ability of the long isoform ZDHHC20L to modify GPX4 and found that it was more efficient than the canonical enzyme in promoting GPX4 acylation (Fig. 8fg). Given the stress-induced expression of ZDHHC20L and its proposed role in redox homeostasis, we next asked whether oxidative stress conditions could modulate GPX4 acylation. Remarkably, H₂O₂ treatment had a major effect on GPX4 acylation, as evidenced by a marked increase in ³H-palmitate incorporation into GPX4 (Fig. 8h).

Because GPX4 activity depends on GSH, and its knockdown increases GSH levels (Fig. 7h), we asked whether ZDHHC20 influences cellular GSH levels. Similar to GPX4 and ZNF354A, ZDHHC20 knockdown elevated intracellular GSH (Fig. 8i). This redox imbalance was fully corrected by re-expression of ZDHHC20L, whereas the canonical isoform had a more modest effect (Fig. 8i). Importantly, ZDHHC20L conferred a marked survival advantage: loss of ZDHHC20 impaired cell viability, consistent with recent findings86, which was rescued by ZDHHC20L and only partially by the canonical form (Fig. 8j). Finally, ZDHHC20L-expressing cells were significantly more resistant to H₂O₂-induced oxidative stress when compared to cells expressing the canonical isoform or lacking ZDHHC20 (Fig. 8j).

Altogether, these findings demonstrate that ZDHHC20 contributes to cellular redox homeostasis, and that ZDHHC20L outperforms the canonical isoform. This identifies ZDHHC20L as a functional effector of the LORD pathway that protects cells against oxidative stress.

Methods
Cell lines
U2OS (ATCC: HTB_96), MDA-MB-231 (ATCC: HTB_26), K-562 (ATCC: CCL_243), SUDHL4 (ATCC: CRL_2957), SUDHL5 (ATCC: CRL_2958), SUDHL6 (ATCC: CRL_2959), MCF7 (ATCC: HTB_22), SW480 (ATCC: CCL_228), LS1034 (ATCC: CRL_2158), HCT116 (ATCC: CRL_3502), HAP-1 (Horizon Discovery: HZGGHC9001), HAP-1 KO_KAP1 (Horizon Discovery: HZGHC000293c003), HEK293T (ATCC: CRL-3216), HEPG2 (ATCC: HB_8065), Calu-3 (ATCC: HTB_55), 3T3 (ATCC: CRL_1658), VERO-E6 (ATCC: CRL_1586) cells were grown in Dulbecco’s Modified Eagle Medium supplemented with 10% FBS, penicillin, and streptomycin. HELA (ATCC: CCL_2) cells were grown in MEM Media supplemented with 10% fetal calf serum, 1% penicillin–streptomycin, 1% NEAA and 1% glutamine (all media from Thermo Fisher Scientific). ZDHHC20 KO HEK293T cells were generated using CRISPR technology38. Cell lines stably expressing ZNF354A or GFP, used for ChIP seq, were generated by lentiviral transduction35. cDNAs were cloned into the doxycycline-inducible pTRE-3HA vector to express C-terminally HA-tagged proteins. Lentiviral particles were produced using standard second-generation packaging vectors (Trono laboratory, https://tronolab.epfl.ch) and used to infect 293T cells (ATCC) at a multiplicity of infection of 0.1. Cells were selected in 1 µg/ml puromycin for 7 days, and expression was confirmed by western blot using anti-HA antibodies35.

Antibodies and reagents
The antibodies and reagents were acquired from: ATF2 (Abcam: ab_131484; RRID: AB_11156678, rabbit: 1:2000x), ATF2 (Abcam: E243 ab32160, RRID: AB_2243137, rabbit: 1:2000x), phosphor-ATF2 (T69) (Abcam: 131106; RRID: AB_11157608; rabbit: 1:1000x), GAPDH (Thermofisher: 398600; RRID: AB_2533438; mouse: 1:4000x), ZDHHC20 (Sigma: SAB4501054; RRID: AB_10744838; rabbit: 1:2000x), HA-HRP (Roche: 112013819001; RRID: AB_390917; rat: 1:5000x), KAP1 (Abcam: ab_109289; RRID: AB_10863057, rabbit: 1:1000x), phosphor-KAP1 S473 was generated in D. TRONO laboratory using the following peptide krsrSgegevsgl (rabbit: 1:500x), Nucleocapside N SARS-CoV-2 (Genetex: GTX135357; RRID: AB_2868464; rabbit 1:4000x), FLAG (Sigma: F3165; RRID: AB_259529; mouse: 1:2000x), phosphor-Threonine-Serine (BD: 612548; RRID: AB_399843; rabbit: 1:1000x), GPX4 for WB (Cell Signaling: 52455; RRID: AB_2924984, rabbit: 1:1000x), GPX4 for IP (MA5-49216, RRID: AB_3074874, mouse 1:2000x), SETDB1 (Novus Biologicals: NBP1_51677; RRID: AB_11002952, mouse: 1:2000x), NRF2 (Abnova: H00004780; RRID: 566020, mouse: 1:2000x), V5-HRP (Sigma: V2260; RRID: AB_261857, mouse: 1:2000x), Actin (Millipore: MAB1501; RRID: AB_2223041, mouse: 1:4000x), MAT1A (Abcam: 129176; RRID: AB_11145300, rabbit: 1:2000x), ZNF354A (Santa Cruz: 81140; RRID: AB_1131557, mouse: 1:1000x), MAT1A (Abcam: ab1129176, RRID: AB_11145300, rabbit: 1:1000x), Myc (Millipore: 9E10, 05-419, RRID: AB_309725, mouse: 1:3000x), and HRP-conjugated secondary antibodies (GE-Healthcare).

RSL-3 (Sigma: S8155), Hydrogen Peroxide 30% (Fisher: H/1750/15), Rotenone (Cayman Chemical: CAY-13995), Ferrostatin-1 (Sigma: SML0583), Bodipy 581/591 C11 (Sigma: D3861), Liperfluo (Fisher: L248), Propidium Iodide (Thermofisher: P3566), Cell Viability assay (Promega: G9711), JQ1 (Sigma: SML-1524), Mithramycin (LKT: M3476), Erastin (Millipore: 329600), all resuspended in DMSO and N-acetylcysteine (NAC) (Selleckchem: S1623) resuspended in water, with pH adjusted to 7.4).

siRNA
For human ZNF354A, 3 different siRNA in 3’-UTR were tested and validated, from Qiagen: ZNF354A (TACATCCTTGAGAGAGATGTA), from Santa Cruz (sc-91974), ZNF354A (GTCACGTGATCATCAGAAA), and from Origene, ZNF354A (GAGGTTTATCCATGGAATTAAATACCT).
siRNAs against all human ZDHHC genes were the same as previously published97.
The other following human siRNA with the corresponding target sequences were purchased from Qiagen: ZNF354B (ATCAGTCTTCATTAAGCAACA; CACATTGAAGAGGACTCCTTA; TACATGCTTGAGTGATTA), ZNF317 (CATGACGGAAATCACACTAAA), ZNF 308 (CAGTTCATTGGCAACCTCATA), ZNF677 (GAGATTGGTTACAGTACAAGA), ZNF793 (ACCCTGGCATGTAAACGTTTA), SETDB1 (TCGGGTGGTCGCCAAATACAA), KAP1 (AGCGTCCTGGCACTAACTCAA), ATF2 (CCGAGGTAGTCCACATACAGAA), NRF2/NFE2L2 (CCCATTGATCTTTCTGATCTA), GPX4 (CGGCTGCGTGGTGAAGCGCTA). The following human siRNA were purchased from Santa Cruz: SP1 (sc-44221), FOXA1 (sc-37930). Mouse siRNA were purchased from Qiagen for mouse ZFP354A (TACCACTTTAATAACATTCAA). As a control siRNA, a sequence targeting the viral glycoprotein VSV-G (5’-ATTGAACAAACGAAACAAGGA-3’) was used. Transfections of 50 nM of siRNA were carried out using TRANSIT-X2 (MIRUS), and the cells were analyzed at least 72 h after transfection.

Western Blotting
Cells were washed three times in 1x PBS at 4°C and lysed in Buffer (1x PBS, 0.5% NP40 and protease inhibitor cocktail; Roche) for 30 min on ice. Lysates were then spin down at 10000 g, and the protein content of supernatant were determined, the samples were boiled in Laemmli buffer for 5 min before separation via SDS-PAGE and western blotting against the different anti-bodies used in this study. For the analysis of phosphorylated proteins, SuperSep™ Phos-tag™ gels (cat. no. 199-18011) were used. Western blots were developed using the ECL protocol and imaged on a Fusion Solo from Vilber Lourmat. Densitometric analysis was performed using the software Bio-1D from the manufacturer.

Plasmids
Plasmids expressing HA-tagged ZNF354A-HA, ZNF317-HA, ZNF677-HA, ZNF793-HA, KAP1-HA were obtained from the D. Trono lab35. Plasmids expressing FLAG-ATF2 (RC2118983) were from Origene, myc-SETDB1 (RC2266620) and plasmids expressing SP1-FLAG (25543) and FOXA1-V5 (153109) from Addgene. Mutations to change KAP1-HA to KAP1-FLAG, ZNF354A-HA to ZNF354A-FLAG, FLAG-ATF2 to HA-ATF2, HA-ATF2 6A (T52A-T69A-T71A-T73A-S490A-S498A), HA-ATF2 6D (T52D-T69D-T71D-T73D-S490D-S498D), ZNF354A-HA (S169A), ZNF354A-HA (S169D), ZNF354A-HA (T189A), ZNF354A (T154A), ZNF354A-HA (D18R-E27R), ZNF354A RA (E45R-N46A), ZNF354A RR-RA (D18R-E27R-E45R-N46A), KAP1-HA (S473A), KAP1-HA (S473D) and MYC-SETDB1 inactive form (H1224A-C1226A-C1279A-C1280A-C1281A) were generated following Quickchange mutagenesis kit (Agilent) instructions. We generated a pIRES-based expression construct encoding the wild-type cytoplasmic isoform 2 of human GPX4, tagged with Myc and Flag RR epitopes. This construct includes a UGA codon at position 46, corresponding to the incorporation site of selenocysteine (Sec, U46), as well as the selenocysteine insertion sequence (SECIS) element in the 3′ untranslated region (3′ UTR). The SECIS element is a conserved RNA stem-loop structure required for the recoding of the UGA stop codon as selenocysteine during translation, enabling the proper synthesis of selenoproteins.

Q-RT-PCR
For the real-time PCR, RNA was extracted from a six-well dish using the RNeasy kit (Qiagen). In all, 0.5-1 mg of the total RNA extracted was used for the reverse transcription using random hexamers and superscript II (Invitrogen). A 1:40 dilution of the cDNA was used to perform the real-time PCR using using Applied Biosystems SYBR Green Master Mix on 7900HT Fast QPCR System (Applied Biosystems) with SDS 2.4 Software. All data (always in triplicate) were normalized to Ct values from three housekeeping (HK) genes ALAS-1, Guss and TBP. Results were expressed as 2^(-ΔΔCt)*100%.

Oligonucleotides for quantitative RT-PCR
All QPCR primers, used in this study were synthesized by Microsynth (Balgach, Switzerland), and are described in detail in table below (Table 1). Primer design was performed using the NCBI Primer Designing Tool https://www.ncbi.nlm.nih.gov/tools/primer-blast/

Aerolysin purification and cell intoxication
Proaerolysin toxin was produced in Aeromonas salmonicida and purified using established procedures98 involving 85% ammonium sulfate precipitation, desalting on a Sephadex G-25 column, and sequential purification by hydroxyapatite and DEAE-Sepharose chromatography. Cells were treated for one h in complete medium with 10 ng/ml of proaerolysin at 37°C. Cells were washed twice in complete medium and further incubated at 37°C for indicated times.

GREAT – analysis
ChIP-seq data for ZNF354A-HA binding sites were obtained from KRABopedia58 and analyzed using the Genomic Regions Enrichment of Annotations Tool (GREAT - http://great.stanford.edu/public/html/)71. Gene regulatory domains were defined as regions extending in both directions from each transcription start site (TSS) to the nearest TSS, up to a maximum of 300kb. Enrichment significance was assessed using GREAT’s binomial test, which estimates the probability of observing the number of submitted regions overlapping a given annotation compared to the fraction of the genome annotated for that term. GO Biological processes statistically overrepresented among genomic regions bound by ZNF354A were depicted.

Human MucilAir assays
MucilAir-human upper respiratory tissues (Epithelix, Geneve, Switzerland) were maintained according to the manufacturer’s protocol. For infection, tissues were washed apically with 200 µl of DPBS, calcium, magnesium (#14040091—Gibco) for 20 min at 37°C and the basal medium replaced with fresh mucilair medium. Tissues were infected at the MOI of 0.1 PFU (assuming the manufacturer’s estimations of 500000 cells per tissue). Tissues were inoculated with 200 µl of SARS-CoV-2 (passage 3) for 3h (apically) at 33°C. The apical inoculum was removed and infected allowed to proceed for the indicated timepoints in DMEM supplemented with 2.5% FCS, penicillin and streptomycin. For harvest tissues were maintained until harvest. For harvest tissues were lysed using 300 µl lysis buffer for 30 min and processed for western blot.

Viral Stock production and titration with plaque-based assays
All viral stocks were produced and isolated from supernatants of Vero E6 cells, cultured in T75 culture flasks to a confluency of 80-90%, and infected with an original passage 2 (P2) SARS-CoV-2 virus, for 48 or 72h, at MOI ≈ 0.05, in 10 ml DMEM supplemented with 2.5% FCS. Original stocks were obtained from the following strain: hCoV-19/Switzerland/GE9586/2020|EPI_ISL_414022|2020-02-27. Passage 3 supernatants were harvested, clear of cell debris by centrifugation (500 g 10 min) and filtration (0.45 µm), aliquoted and stored at −80 C. Viral titers were quantified by determining the number of individual plaque forming units after 48h of infection in confluent Vero E6 cells as described in ref. 37.

SARS-CoV-2 infections
All infections for experimental analysis were done using passage 3 SARS-CoV-2 stocks. Vero E6 cells or CALU-3 cells seeded to a confluency of 90 to 100%, were, washed twice in warm serum-free medium and inoculated with the indicated MOI of SARS-CoV-2, diluted in serum free medium. 1h after inoculation cells were washed with complete medium and infection allowed to proceed for the indicated timepoints in DMEM supplemented with 2.5% FCS, penicillin and streptomycin.

Drug and toxin treatments
All drug treatments were done for the indicated times in complete culture and/or infection medium. Equivalent volume of Dimethyl sulfoxide (DMSO), used as a solvent, was added for control samples. Specifically, culture media was replaced, cells were washed once in warm culture media and drugs resuspended as indicated were used as: RSL3 (in DMSO - 3 µM, increasing concentrations 0.6 to 10 µM), Ferrostatin-1 (DMSO - 1–15 µM), H₂O₂ (0.5–100 µM), Rotenone (1–10 µM).

Data mining analysis
UCSC genome browser at ZDHHC20 locus was obtained from (Human version hg19). Specific UCSC genome browser tracks were selected for display in Figs. 1 and 2. Transcript annotation corresponds to GENCODE Genes track (version V40 lift37); Histone Modifications by ChIP-seq from ENCODE/Stanford/Yale/USC/Harvard display ChIP-seq signals for H3K4me1, H3K4me3, H3K27Ac marks for HepG2 and H3K9me3 for U2OS. Transcription Factor CHIP-seq Peaks track shows transcription factor SETDB1, and KAP1 binding sites for U2OS and K562 cells based on ChIP-seq experiments from ENCODE. KZFP CHIP-seq data show binding sites for different KZFP proteins obtained from KRABopedia (https://tronoapps.epfl.ch/web/krabopedia/) (https://doi.org/10.1101/2023.02.27.530095)

Chromatin Immunoprecipitation (ChIP) followed by qPCR or sequencing (ChIP-seq)
K562 cells (30 million) were cross-linked at room temperature for 10 minutes by adding formaldehyde to a final concentration of 1%, followed by quenching with glycine Tris 200 mM. Cells were washed twice with PBS, pelleted, and stored at −80°C. Pellets were sequentially lysed in LB1 (50 mM HEPES-KOH pH 7.4, 140 mM NaCl, 1 mM EDTA, 0.5 mM EGTA, 10% glycerol, 0.5% NP-40, 0.25% Triton X-100, protease inhibitors), LB2 (10 mM Tris-HCl pH 8.0, 200 mM NaCl, 1 mM EDTA, 0.5 mM EGTA, protease inhibitors), and SDS shearing buffer (10 mM Tris-HCl pH 8.0, 1 mM EDTA, SDS 0.15%, protease inhibitors). Chromatin was sonicated (Covaris: 5% duty, 200 cycles, 140 PIP, 20 min 25 min) to obtain DNA fragments of 100–300 bp. ChIP was performed anti-HA magnetic beads (Pierce: 88837). Chromatin was adjusted for immunoprecipitation using 1% Triton X-100 and 150 mM NaCl then transferred on beads, followed by overnight incubation at 4°C. Immunoprecipitated complexes were washed sequentially with Low Salt Wash Buffer (10 mM Tris-HCl pH 8.0, 1 mM EDTA, 150 mM NaCl, 1% Triton X-100, 0.15% SDS, protease inhibitors), High Salt Wash Buffer (10 mM Tris-HCl pH 8.0, 1 mM EDTA, 500 mM NaCl, Triton X-100, 0.15% SDS, protease inhibitors), LiCl Buffer (10 mM Tris-HCl pH 8.0, 1 mM EDTA, 0.5 mM EGTA, 250 mM LiCl, 1% NP-40, 1% NaDOC, protease inhibitors), and TE buffer. DNA was eluted and purified using QIAGEN columns. Experiments were performed in biological duplicates, Samples were send for sequencing and ChIP-QPCR experiments were independently repeated 3 or 4 times for each depicted primer.
ChIP and input DNA were analyzed by qPCR using specific primers and sequencing. Enrichment was calculated as a percentage of input or relative to a control region using the ΔΔCt method. Primers used for QPCR are listed below:

Library preparation and sequencing
DNA concentrations were determined using a Qubit fluorometer (Thermo Fisher Scientific) following the manufacturer’s protocol. Chromatin immunoprecipitated DNA was processed using the NEBNext Ultra II DNA Library Prep Kit (New England Biolabs, Version 7.0_9/22) according to the manufacturer’s instructions (internal experiment code GFX016). Input DNA amounts varied between 1.5 ng and 5 ng, as specified in the corresponding sample table. Given the absence of initial DNA profile data, a positive control was included during library preparation. Library concentrations were measured using Qubit High Sensitivity (HS) DNA quantification, and fragment size distributions were assessed using a TapeStation TS4200 (Agilent Technologies). All libraries exhibited expected fragment profiles and sufficient yield for sequencing. Prepared libraries were sequenced on the Element Biosciences Aviti platform in a paired-end 150bp (PE150) run (run ID: AVT0149). Sample-specific identifiers and sequencing metadata are detailed in the supplementary data. Adapter sequences were trimmed using Cutadapt vX.X with TruSeq adapter sequences:
Read1: AGATCGGAAGAGCACACGTCTGAACTCCAGTCA;
Read2: AGATCGGAAGAGCGTCGTGTAGGGAAAGAGTGT

ChIP seq analysis
To identify and merge significant peaks across multiple conditions, we utilized BEDTools99 (v2.30.0). Initially, overlapping peaks from multiple BED files were merged using the bedtools multiinter function. To ensure a more comprehensive peak detection, an alternative strategy was applied, merging all available BED files in the directory. Following peak merging, signal intensity filtering was performed using deepTools (v3.5.1). The computeMatrix function extracted signal values from bigWig (BW) files over predefined peak regions (Filt_GFP.bed). A threshold of 15 was applied to exclude peaks with excessively high signal intensities. To visualize the signal distribution, a heatmap was generated using plotHeatmap, employing the Oranges_r colormap. Based on the filtered set (sorted_regionsFilt12.bed), another round of peak merging was conducted to ensure that only the most relevant peaks were retained. This final merged peak list contained only peaks present in HEK293T and those retained in K562. To further refine peak selection and exclude aberrant values, we applied an additional filtering step with a stricter intensity threshold (--maxThreshold 150). A final heatmap was generated to visualize the refined peak set. A final heatmap was generated to visualize the refined peak set. Ultimately, the final set of high-confidence peaks used for downstream analysis was stored in sorted_regions_3.bed, representing the most relevant and biologically meaningful peak regions across conditions.

RNA seq
RNA quality was controlled on the TapeStation 4200 (Agilent), which confirmed their integrity. Libraries for mRNA-seq were prepared with the Stranded mRNA Ligation method (Illumina), according to manufacturer’s instructions, starting from 800 ng RNA. Libraries, all bearing unique dual indexes, were subsequently loaded at 100 pM on a Novaseq 6000 flow cell (Illumina) and sequenced according to manufacturer instructions, yielding pairs of 60 nucleotides reads at a depth of about 70 mio reads pair per sample. Reads were trimmed of their adapters with bclconvert v00.000.000.3.9.3 (Illumina) and quality-controlled with fastQC v0.11.9. FastQScreen v0.14.0 tool was used for screening FASTQ files reads against multiple reference genomes.

RNA seq processing and analysis
Sequencing reads were mapped to the human hg19 genome using hisat2 [D. Kim, B. Langmead, and S. L. Salzberg, “HISAT: a fast spliced aligner with low memory requirements,” Nature Methods, vol. 12, no. 4, pp. 357–360, Mar. 2015.]100 with parameters: hisat2 -k 5 --seed 42 --rna-strandness RF. Counts on genes were generated using featureCounts [Y. Liao, G. K. Smyth, and W. Shi, “featureCounts: an efficient general purpose program for assigning sequence reads to genomic features,” Bioinformatics, vol. 30, no. 7, pp. 923–930, Apr. 2014.]. Only uniquely mapped reads were used for counting on genes. Normalization for sequencing depth was done using the TMM method as implemented in the limma package of Bioconductor [Gentleman et al., 2004]. Differential gene expression analysis was performed using voom (Law et al., 2014) as it has been implemented in the limma package of Bioconductor. A gene was considered to be differentially expressed when the fold change between groups was bigger than 2 and the p-value was smaller than 0.05. A moderated t-test (as implemented in the limma package of R) was used to test significance. P-values were corrected for multiple testing using the Benjamini-Hochberg’s method97. Gene set enrichment analysis (GSEA) was performed using the ClusterProfiler package in R. The analysis utilized a ranked list of genes and gene set collections downloaded from MsigDB. The GSEA was conducted with the following parameters: the number of permutations was set to 10,000, minimum gene set size was 10, maximum gene set size was 800.

Flow cytometry analysis of membrane permeability and lipid peroxidation
U2OS cells (1×106 per well, 6-well plate) were transfected with siRNA for 72h. For Liperfluo staining (Dojindo), cells were treated with 5 µM RSL-3 for 24h, washed twice with EBSS-10 µM HEPES, and incubated in 1 mL EBSS-HEPES with 5 µM Liperfluo for 30 min at 37°C. Cells were washed, trypsinized, washed in 1% FBS EBSS-HEPES to remove trypsin, resuspended in 500 µL EBSS-HEPES, filtered, and stained with propidium iodide (1 µg/mL) prior to flow cytometry. For C11-BODIPY 581/591 (Invitrogen) staining, siRNA-treated cells were washed twice in HBSS and incubated in 1 mL HBSS with 10 µM probe for 30 min at 37°C. Excess dye was removed and cells were treated with 5 µM RSL-3 for 4h in complete medium. Cells were then processed as above but stained with DAPI (1 µg/mL). Flow cytometry was performed on an LSRII or LSR Fortessa (BD Biosciences). Oxidized Liperfluo and BODIPY were detected using 488 nm excitation and 530/30 nm emission; PI and reduced BODIPY were detected using 561 nm excitation and 610/20 nm emission. At least 10,000 live events (PI/DAPI-negative) were acquired per sample and data were analyzed using FlowJo.

CLICK-PEG Assay
The protocol was adapted from88. Twenty-four h after transfection, cells were washed with serum-free medium containing 1 mg/mL BSA and incubated for various times with either 100 µM unlabeled palmitic acid (control) or 100 µM palmitic acid-azide. After labeling, cells were washed twice with cold PBS and lysed in 50 mM Tris-HCl (pH 8.0), 0.5% SDS. Lysates were subjected to a click reaction with 5 kDa mPEG-alkyne (JKA-3177, Sigma), CuSO₄, TBTA, and ascorbic acid for 1h at room temperature. The reaction was stopped by boiling the samples in 4× SDS–BME sample buffer (SB 4×).

Intracellular glutathione measurements
Intracellular reduced glutathione levels were measured using the QuantiChrom Glutathione Assay Kit (DIGT-250, BioAssay Systems), following the manufacturer’s instructions. Briefly, 1×106 cells were collected and processed for the colorimetric detection of reduced glutathione. The assay is based on the reaction of glutathione with 5,5′-dithiobis-(2-nitrobenzoic acid) (DTNB), which yields a yellow-colored product. Absorbance was measured at 412 nm, and values were directly proportional to the glutathione concentration in the sample.

3H-palmitic acid radiolabeling experiments
Hela cells were transfected or not with different constructs, incubated for 2h in Glasgow minimal essential medium (IM; buffered with 10 mM HEPES, pH 7.4) with 200 µCi/ml of 3H palmitic acid (9,10-3H[N]) (American Radiolabeled Chemicals, Inc.). The cells were washed, and incubated in DMEM complete medium for the indicated time of chase or directly lysed for immunoprecipitation with the indicated antibodies. After immunoprecipitation, washed beads were incubated for 5 min at 90°C in reducing sample buffer prior to 4–20% gradient SDS-PAGE. Gels were incubated 30 min in a fixative solution (25% isopropanol, 65% H2O, 10% acetic acid), followed by a 30 min incubation with the signal enhancer Amplify NAMP100 (GE Healthcare). The radiolabeled products were imaged using a Typhoon phosphoimager and quantified using a Typhoon Imager (ImageQuan Tool, GE Healthcare). The images shown for 3H-palmitate labeling were obtained using fluorography on film.

DSS-induced mice colitis
Six wild-type C57BL/6j mice (8-week-old males) were used. Three (n = 3) mice were used as controls and three mice were given 3% dextran sulfate sodium in the drinking water for 7 days, then switched to regular drinking water for 3 days. Three Control 8-week male were given drinking water that did not contain DSS. During the 10-day experiment, mice were weighted, and disease activity index (DAI) was performed daily based on stool consistency, presence of occult blood and body weight loss. On day 10, mice were euthanized with pentobarbital injections and bled via cardiac puncture, and colons and intestines were collected. For animal experimentation, all procedures were performed according to protocols approved by the Veterinary Authorities of the Canton Vaud and according to the Swiss Law (license VD3497, EPFL).

Quantification and Statistical Analysis
All Western blots were independently repeated at least three times. When quantitative data are presented, individual data points represent independent biological replicates, and the number of replicates (n) is indicated in the corresponding figure legends. For representative experiments (e.g., cell death assays), the number of technical replicates is specified, and each experiment was repeated independently at least three times with similar results. Statistical evaluations were carried out using GraphPad Prism software, with graphical representations and detailed statistical information available in the figure legends. For ANOVA, p values were calculated using post hoc tests: Tukey’s and Sidak’s for multiple comparisons between groups, and Dunnett’s for comparisons against a control condition. RNA-seq and ChIP-seq analyses were performed using distinct bioinformatics pipelines, as outlined in the Materials and Methods section, to ensure appropriate data handling and statistical evaluation specific to each dataset. Exact p values are indicated when available. For comparisons analyzed in GraphPad Prism, p values below 0.0001 are reported as p<0.0001. Details of statistical analyses and source data are provided in the accompanying data source file.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "In the present study, Mesquita et al. investigated the phosphorylation-dependent regulation, complex assembly, and downstream transcriptional control of the non-canonical epigenetic regulatory complex ATF2-KAP1-SETDB1-ZNF354A, which governs the proposed “Lipid Oxygen Radical Defense (LORD)” pathway. The authors demonstrated that under oxidative stress, ATF2, KAP1, and ZNF354A undergo phosphorylation in a p38- and JNK-dependent manner, leading to the dissociation of ZNF354A from both the complex and its chromatin targets. This dissociation licenses expression of the ZDHHC20 long isoform and several antioxidant genes, thereby protecting cells from oxidative stress-induced damage, including drug-induced ferroptotic cell death.\nOverall, addressing the genetic and epigenetic basis of oxidative lipid radical sensing and defense has significance and is timely. The present study defines an epigenetic regulatory complex that mediates cellular oxidative stress responses involved in key biological processes potentially including aging, cancer, and inflammation. The authors used a variety of methodologies including ChIP-seq, RNA-seq, biochemistry, and cellular assays to support their conclusions. The experimental designs are largely comprehensive, with extensive controls included using point-mutated proteins.\nNevertheless, several points appear unclear and await further clarification.\nMajor comments:\nQ1: What are the direct biological consequences of ZDHHC20L expression in terms of redox homeostasis? How much contribution does ZDHHC20L have to the regulatory effects of ZNF354A on oxidative stress and ferroptosis?\nQ2: While Fig. 2g suggests that KAP1 phosphorylation is sufficient to induce ATF2 phosphorylation, the ATF2-6D overexpression data and subsequent ERK inhibitor experiments appear to position ATF2 as the upstream regulator. Could the authors provide clarification on this part of the data interpretation?\nQ3: The authors may consider toning down their use and claims of the term \"Lipid Oxygen Radical Defense (LORD) pathway\" since this is the exact part of the manuscript that lacks sufficient direct evidence. For instance, what are the major effectors of LORD, ZDHHC20L, SLC7A11, or other selenite proteins?\nQ4: In the author’s previous paper, although ZDHHC20 regulates GPX4 palmitoylation and therefore regulates GPX4 activity, there lacks of direct comparison on the activities between ZDHHC20 and ZDHHC20L. Can ZDHHC20L also regulate GPX4 activity?\nQ5: In Fig5e, aerolysin is a pore-forming protein. Can aerolysin treatment trigger lipid peroxidation and ferroptosis? The authors need to show BODIPY-c11 staining results upon aerolysin treatment. Also, the authors should validate whether (and the exact) “selenium metabolic process” related genes are upregulated upon LORD pathway activation.\nQ6. Regarding the specificity of the explored pathway in oxidative lipid radical responses, in Fig. 7f, Fer-1 can’t fully rescue the cell death induced by ZNF354A-OE. Is ZNF354A-OE also inducing other cell death? Consistent with this possibility, in Fig. 7g, NAC can almost fully rescue the ZNF354A-OE induced cell death. Can the authors provide an estimation for the relative contributions of lipophilic versus cytosolic ROS in their indicated context?\nMinor comments:\nQ1. In Fig. 4e and subsequent text (e.g., line 491), System Xc⁻ also includes the SLC3A2 protein component. Although not revealed as a downstream target of ZNF354A, labeling it in the figure (and/or text) would be more accurate.\nQ2. For more rigorous determination of ZNF354A and its mutant ZNF354Amut in regulating ferroptosis sensitivity, the siControl group should be included for comparative analysis in Fig. 7e and 7f.\nQ3. Fig. 7a and b, the RSL3 induction of the BODIPY-c11 signal is quite weak. The authors should try higher concentration or longer treatment time, or clarify the data interpretations. Also, adding viability assay on ZNF354A-KD upon RSL3 treatment with Lip1/Fer1 rescue is recommended.\nQ4. There is inconsistency on data presentation. Some data use SEM, while some use SD. The authors should clarify in the methods or Figure legends how each is chosen or stick to one presentation method.\nQ5. Line 226, “some 380 of which are…”, it is unclear what is indicated here.\nQ6. Line 419, typo in NRF2", "reviewer_2": "Summary:\nReactive oxygen species (ROS) are natural byproducts of metabolism that can cause oxidative stress and damage to lipids in cell membranes. This can lead to ferroptosis, a form of non-apoptotic cell death in cancer, neurodegeneration, and aging. Transcription factors like NRF2, and antioxidant systems are involved in detoxification and lipid protection as cellular defense. However, gaps remain in understanding how lipid-specific antioxidant responses are controlled.\nIn this manuscript the authors demonstrate:\n1. Using ENCODE data, that stress activated transcription factor ATF2 binds upstream of ZDHHC20L, a dynamically induced maker of stress response.\n2. siRNA against ATF2 reduced ZDHHC20L expression in response to the bacterial pore forming toxin aerolysin.\n3. ATF2 phosphorylation is observed in conjunction with ZDHHC20L induction, phosphomimics of ATF2 directly induce ZDHHC20L.\n4. silencing of Atf2 increased sensitivity to aerolysin, which could be rescued by WT but not phospho-mutants of ATF2.\n5. siRNA /KO of SETDB1 or KAP1 activates ZDHHC20L.\n6. ZNF534A binding sites overlapsa repressive region upstream of ZDHHC20L, siRNA against ZNF534A activates ZDHHC20L, (siRNA against other KZFPs had no effect).\n7. ATF2 coprecipitated with KAP1. The ZNF534a-KAP1 interaction is disrupted by aerolysin or by 6D mutant expression of ATF2.\n8. KAP1 Ser473 is detected in response to aerolysin, mutations of this site kills phoshorylation and prevents activation of ZHHC20L… phosphomimics triggered ATF2 phosphorylation and ZDHHC20L.\n9. ZNF534a is also phosphorylated in response to aeroslysin, which is dependent on ATF2 phosphorylation.\n10. Phosphorylation of all complex members is dependent on p38 and Jnk.\n11. Znf534a and its regulation of ZDHHC20L is conserved in mice.\n12. ZNF354a binds and represses genes involved in antixodant response, and is evicted in response to peroxide.\n13. Manipulating ZNF354 expression levels or engineering functional mutants alters sensitivity to ferroptosis.\nOverall this was an exceptional study that identifies and characterizes a novel epigenetically regulated defense mechanism, they call LORD (Lipid Oxygen Radical Defense), with ZNF354A, a KZFP, as a master regulator. Their experiments convincingly demonstrate that ZNF354A represses oxygen radical defense genes via KAP1, SETDB1, and ATF2, and that Lipid peroxide accumulation disrupts this complex, dissociating ZNF354A from it’s protein partners and target genes, which activates ZDHHC20 Long (ZDHHC20L) and many additional regulators that modulate sensitivity to stress induced cell death via ferroptosis. This discovery could be a potential target for therapeutic intervention in a variety of conditions such as chronic inflammation, infections, cancer, and aging-related disorders.\nQuestion that should be addressed for a revised version\n1. Line 270-272….I am confused, I can see how the phosphomimic KAP1 would activate ZDHHC20L, but how do the authors propose the KAP1 phosphomimic causes ATF2 phosporylation?\n2. Figure 1C, I can’t tell whether the red and purple indicate KAP1 and SETDB1 or U2OS and K562? Should Plot the signal or peaks for each protein in each cell type.\n3. Based on the KRABopedia, and limited discussion in the paper, ZNF345a is a conserved ancient mammalian KZFP that has at least some conserved activities in mice and humans (such as the regulation of ZDHH20L). However there is almost no discussion that this protein appears to bind several related family members of ancient mammalian L1s. The authors should provide more analysis of their ChIP-seq data to demonstrate whether the effects on genes are due to the distribution of these L1s near target genes. It would also be very interesting to analzye conservation in the gene networks across species ie in mice and humans and whether it can be explained by conservation in the distribution of the L1s and the their target motifs.", "reviewer_3": "I am a researcher in the field of KRAB zinc finger proteins with 15 years of experience. I've enjoyed reading the manuscript titled \"Identification of the Lipid Oxygen Radical Defense pathway and its epigenetic control\" - it is a well crafted, novel and convincing work that fully deserves publication in Nature Communications.\nThe authors describe in it a defense pathway against ROS-triggered lipid damage, and most interestingly that this is under epigenetic control of a mammalian-conserved KRAB zinc finger, ZNF354A. Overall the authors present copious supportive biochemical evidence for their model and it is one of the most cogent manuscripts I had to review in the past few years.\nHowever, I have some issues with interpretation of some results and provide here comments for authors to adjust before publication of the work.\nMajor comments:\nThe only part of the authors logical flow that I find not convincing is the claim that ATF2 is part of a 'supercomplex' with KAP1 and ZNF354A. Similar 'complexes' of KAP1 with multiple transcription factors have been suggested in the past with most popular transcription factors (STAT1, p53, and many others) and these models suffer from first-order interpretation of immunoprecipitation assays against KAP1 and/or first-order interpretation of results coming from loss of the transcription factor and the indirect effects this can have on the cell - this paper does both. Upon careful consideration of the data presented, we cannot exclude that a simpler model could be that ATF2 is bound nearby ZNF354A and therefore an IP for either KAP1 or ATF2 will find the other one as they are linked through DNA they bind. In my experience DNAse/benzonase treatment are not sufficient to remove this as the transcription factors can protect a small region of DNA. The data presented in figure 2 panel D shows that ATF2 presence is necessary for loss of ZNF354A at the protein level, which is most interesting, but this could be via indirect effects of ATF2-mediated transcription of other targets (genes or non-coding RNAs). The easiest solution would be for authors either remove all claims of a non-cannonical / supercomplex / subcomplex / necessity of direct binding to ATF2 for repression and discuss the above leaving room for interpretation, or if they insist on the necessity of providing a model, to provide evidence that ATF2 is necessary for deposition of H3K9me3 at ZNF354A bound sites (i.e. perform an H3K9me3 ChIP-seq assay in cells treated with siRNA targeting ATF2 and show that repression is lost). Additionally, if short timescale data of ZNF354A protein levels following loss of ATF2 with a degron system (15-60 minutes) could be obtained the model could be more convincing, as it would be possible to test if ATF2-mediated transcription of other targets is necessary. Additionally, if the model is kept and is as presented in panel j of figure 2, authors should explain why ATF2 would not be carried by KAP1 at all KZFP binding sites. I think removal of this claim would not diminish the value of the manuscript in any way as it is tangential to the main discovery.\nIn most mammalian species ZNF354A has a paralog, ZNF354B, which has almost the same zinc finger array and is therefore expected to bind most if not all of the same targets. Most importantly, ZNF354B has very high expression levels in most cell types. The authors should discuss this and provide future plans to study both independently. Most importantly, they should also provide information and/or experiments to prove that their siRNA against ZNF354A is not also targeting ZNF354B - the same for other reagents if relevant. If reagents are found to target both, I think it would be acceptable to discuss them as paralogs that can provide redundancy and I don't think studying both independently is absolutely necessary for this first manuscript on the topic.\nThe authors don't discuss the binding of ZNF354A versus transposable elements anywhere in the manuscript - I find this surprising since the Trono lab is co-author on the manuscript - according to Krabopedia it is enriched in mammalian-conserved L1 elements, as is ZNF354B. The manuscript should at least mention this and provide an analysis (maybe in supplemental) of the status (transposable element or not?) of the most important binding sites identified. This would enrich the finding with context about evolution of the gene regulatory network that is proposed.\nThe term 'master regulator' is overused - if anything in your model ATF2, and not ZNF354A, is the master regulator, as it activates the targets in the networks and is necessary for loss of ZNF354A-mediated repression.\nDiscuss future experiments performing an RNA-seq in aerolysin-treated cells without ZNF354A and following short term dynamics of induction of the network, along with a timecourse of loss of H3K9me3 at these sites upon stress to test the hypothesis that repression is there to prevent a rapid response, but allow for a delayed one\nMinor comments:\nPlease change all instances of KAP1 to TRIM28 as it is the officially recognized name\nline 29 - \"It is epigenetically repressed, by a complex comprising\" - the comma is unnecessary\nFigure 1 - improve annotation of gene track panels in the manuscript, it is unclear at first sight where the long isoform starts from, especially when viewing the figure not fully zoomed in\nline 167 - \"Active promoter marks, H3K27Ac and H3K4me3, were found, flanking these repressive regions\" - these commas are not necessary\nline 237 - \"The specificity for ZNF354A was further established by immunoprecipitation (IP) experiments against KAP1 using U2OS cells overexpressing irrelevant KZFPs.\" - rephrase to 'overexpressing ZNF354A or two other irrelevant KZFPs as controls'\nlayout of figure 2 is hard to follow between panels - consider having panel d in place of e, and present e on a line below as an horizontal instead of vertical panel\nline 390 - please calculate enrichment of presence near upregulated genes to test if more than expected by chance. Also provide clarity in the directionality of differentially regulated genes\nIn the discussion section, add a sentence or two on the pattern of expression of ZNF354A and what that could mean for regulation of the gene network it controls if cells express it or not.\nFigure 4A - the color legend for the p-value scale should be rescaled to something meaningful", "reviewer_4": "I co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part of the Nature Communications initiative to facilitate training in peer review and to provide appropriate recognition for Early Career Researchers who co-review manuscripts."}, "author_response": "Point by point reply to the reviewers\nReply to Reviewer #1\nWe are happy that the reviewer finds our work on “addressing the genetic and\nepigenetic basis of oxidative lipid radical sensing and defense” of significance and\ntimely.\n1: What are the direct biological consequences of ZDHHC20L expression in terms of\nredox homeostasis? How much contribution does ZDHHC20L have to the regulatory\neffects of ZNF354A on oxidative stress and ferroptosis?\nIn the initially submitted manuscript, expression of ZDHHC20L was merely used as a\nproxy, or readout, to identify the ZNF354A-mediated pathway. We, however, agree\nwith the reviewer that evidence that ZDHHC20L is an effector of the pathway would\nconstitute a significant addition to the paper. We therefore provide significant\nadditional data, corresponding to a full extra figure (Fig. 8). Fig. 8 includes the\nfollowing data, as well as the data described in response to Points 3 and 4:\n- Viability data showing that ZDHHC20 KD cells are more sensitive to H O\n2 2\nthan control cells, and that recomplementation with ZDHHC20L restore\nsensitivity to that of control cells (Fig. 8j).\n- Viability data showing that cells ZDHHC20 silenced cells have reduced\nviability when compared to controls, which could again be restored when\nrecomplementing with ZDHHC20L but with little effect of recomplementation\nwith canonical ZDHHC20 (Fig. 8j). Associated with the viability data we\ndemonstrate that ZDHHC20L is the main enzyme S-acylating GPX4, which\nwas recently found to pe critical to GPX4 stability (see response to point 4).\n- Measurements of glutathione showing that silencing of ZDHHC20, as\nsilencing of GPX4, leads to an increase in the cellular glutathione\nconcentration (Fig. 7h and 8i), and that recomplementation with ZDHHC20L\nrestored normal glutathione levels (Fig. 8i). Canonical ZDHHC20 had a mild\neffect (Fig. 8i).\nThese data show that ZDHHC20L influences cellular redox homeostasis in a way\nthat impacts cell viability and sensitivity to H₂O₂. Future studies will be required for a\nfull understanding of the biological consequences of ZDHHC20L expression on\nredox balance and clarify its role in mediating the effects of ZNF354A on oxidative\nstress and ferroptosis.\n2: While Fig. 2g suggests that KAP1 phosphorylation is sufficient to induce ATF2\nphosphorylation, the ATF2-6D overexpression data and subsequent ERK inhibitor\nexperiments appear to position ATF2 as the upstream regulator. Could the authors\nprovide clarification on this part of the data interpretation?\nOur interpretation is indeed that ATF2 is the upstream regulator and ATF2\nphosphorylation is required for the subsequent phosphorylation of KAP1. We have\nnow clarified this in the results discussing Fig. 2c, and elsewhere in the manuscript.\nWe have removed the blot in Fig. 2g showing that the phospho-mimetic mutant of\nKAP1 can trigger phosphorylation of ATF2 because we currently have no\n1\nmechanistic insight into this and this information is not necessary for the conclusions\ncurrently drawn from this figure.\n3: The authors may consider toning down their use and claims of the term \"Lipid\nOxygen Radical Defense (LORD) pathway\" since this is the exact part of the\nmanuscript that lacks sufficient direct evidence. For instance, what are the major\neffectors of LORD, ZDHHC20L, SLC7A11, or other selenite proteins?\nWe have toned down the use of the term “LORD” throughout the manuscript, and\nnow only mention it later this the paper.\nAs described in our responses to Points 1 and 4, we now provide direct evidence\nthat ZDHHC20L is an effector of the LORD pathway. In response to Point 4, we\nshow that one of the targets of ZDHHC20L is GPX4 (Fig. 8a–d), a key enzyme in\ndetoxifying lipid peroxides.\nIn addition, as detailed in response to Point 5, qPCR analysis now demonstrates that\nsilencing of ZNF354A leads to increased expression of several antioxidant genes,\nincluding SLC7A11, while overexpression of ZNF354A represses these genes\n(Suppl. Fig. 4c–d).\nWe feel that the comprehensive characterization of additional LORD effectors goes\nbeyond the scope of this first study and will require multiple in-depth mechanistic\ninvestigations. However, to illustrate the potential complexity of this pathway, we\nwish to share additional unpublished observations with the reviewer. We have found\nthat several proteins involved either in activation of the pathway, implicated as\neffectors through expression profiling, or known to participate in redox\nhomeostasis, undergo S-acylation in a ZDHHC20-dependent manner. These include\nATF2, SLC7A11, and SLC3A2, which are substrates of both canonical ZDHHC20\nand the stress-induced ZDHHC20L isoform.\nDeciphering the functional consequences of acylation on these proteins—and how\nthis modification contributes to redox homeostasis—will be the focus of future\nstudies.\nFigure for the reviewers: ZDHHC20-mediated acylation of LORD-related proteins.\nParental HEK293, ZDHHC20 derived KO cells, and KO cells recomplemented with canonical or\nthe Long isoform of ZDHHC20 were submitted to the Acyl-RAC method which allows to capture\nS-acylated proteins. This method is based on the fact that the thioester bond that links the acyl\nchain to an S-acylated protein can be broken by hydroxyalamine (+HA) treatment. The thus freed\ncysteine residues can then be captured with thiol-reactive beads. Samples can subsequently be\nanalysed by western blotting against proteins of interest. The figure illustrates that as\nabolished in ZDHHC20 KO cells, and that these proteins are substrates of both the canonical\nform and the LORD-regulated Long form. SP1 was added as a non-acylated control.\n4: In the author’s previous paper, although ZDHHC20 regulates GPX4 palmitoylation\nand therefore regulates GPX4 activity, there lacks of direct comparison on the\nactivities between ZDHHC20 and ZDHHC20L. Can ZDHHC20L also regulate GPX4\nactivity?\nThere appears to be some confusion. The study describing ZDHHC20-mediated\nacylation of GPX4 was published by another group (Huang et al., PMID: 39833225)\nwhile we were independently investigating GPX4 S-acylation. In fact, two studies\nwere published—one identifying ZDHHC20 and the other ZDHHC8 as the modifying\nenzyme—both showing that S-acylation is critical for GPX4 function in vivo,\nparticularly in the context of cancer.\nWe have now added our data (Fig. 8) on the identification of the GPX4 S-acylating\nenzyme as well as the comparison between ZDHHC20L and the canonical form:\n A siRNA screen of all 23 human ZDHHC enzymes shows that GPX4 is\nmodified specifically by ZDHHC20 in our system; we did not observe a role for\nZDHHC8, but maybe there is a context-specific situation in cancer.\n ZDHHC20L acylates GPX4 more efficiently than the canonical ZDHHC20\nisoform, based on incorporation of [³H]-palmitate, suggesting that stress-\ninduced expression of ZDHHC20L (via the LORD pathway) enhances GPX4\nactivity and/or turnover.\n H₂O₂ treatment strongly increases [³H]-palmitate incorporation into GPX4,\nconsistent with the idea that oxidative stress boosts ZDHHC20L activity and\nGPX4 acylation.\nThese results support the conclusion that ZDHHC20L is a functional effector of the\nLORD pathway, modulating GPX4 activity under oxidative stress conditions.\n5: In Fig5e, aerolysin is a pore-forming protein. Can aerolysin treatment trigger lipid\nperoxidation and ferroptosis? The authors need to show BODIPY-c11 staining\nresults upon aerolysin treatment. Also, the authors should validate whether (and the\nexact) “selenium metabolic process” related genes are upregulated upon LORD\npathway activation.\nAerolysin, as other pore-forming toxins, triggers a plethora of response pathways (as\nwe and others have shown) and we were initially surprised that ATF2 actually had\nany detectable effect on aerolysin-induced cell death. So this was very interesting.\nBoth Bodipy-c11 and Liperfluo staining on aerolysin treated cells unfortunately led to\nunusual changed in the behavior of the probes, affecting data interpretation. We\ntherefore did not add this data. We however tested the effect of ferrostatin on viability\nof aerolysin-treated cells as now shown in the Supplementary Fig. 5c. Fer-1 leads to\na partial rescue of aerolysin induced death, consistent with the effect observed upon\nATF2 silencing. This is effect is particularly visible in cells overexpressing ZNF354A,\nwhen the homeostatic level of the pathway’s expression is reduced.\nrelated genes mentioned in Supplementary Fig. 4cd. The data shows that most\ngenes are upregulated. We also performed qPCR analysis upon overexpression of\nZNF354A, which shows that the same genes are down regulated under these\nconditions. So this subset of redox-related genes are regulated by ZNF354A.\n6. Regarding the specificity of the explored pathway in oxidative lipid radical\nresponses, in Fig. 7f, Fer-1 can’t fully rescue the cell death induced by ZNF354A-\nOE. Consistent with this possibility, in Fig. 7g, NAC can almost fully rescue the\nZNF354A-OE induced cell death. Can the authors provide an estimation for the\nrelative contributions of lipophilic versus cytosolic ROS in their indicated context?\nWe have repeated the viability experiments adding ferrostatin-1 to the cells every\nday and transfected ZNF354A leading to 85% cell death after 4 days\n(Supplementary Fig. 7g). Under these conditions, Fer-1 reduced ZNF354A\noverexpression-induced cell death to 22±16%, not significantly different to the\nreduction induced by NAC of 12±5%, while Fer-1+NAC reduced cell death to 7±1%.\nThis analysis indicates that lipophilic ROS contributes to approx. 74%, consistent\nwith the rescue through expression of FSP1, and 12% through cytosolic or other\nROS. This is now mentioned in the manuscript.\nWe found that zVAD-fmk (used at 10uM) had no effect, ruling out a role for apoptosis\n(not mentioned in the manuscript).\nMinor comments:\n1. In Fig. 4e and subsequent text (e.g., line 491), System Xc⁻ also includes the\nSLC3A2 protein component. Although not revealed as a downstream target of\nZNF354A, labeling it in the figure (and/or text) would be more accurate.\nWe have added SLC3A2 in the figure.\n2. For more rigorous determination of ZNF354A and its mutant ZNF354Amut in\nregulating ferroptosis sensitivity, the siControl group should be included for\ncomparative analysis in Fig. 7e and 7f.\nThe control plasmid experiments were shown in the supplementary figures. We now\nmention this in the legend of Fig. 7.\n3. Fig. 7a and b, the RSL3 induction of the BODIPY-c11 signal is quite weak. The\nauthors should try higher concentration or longer treatment time, or clarify the data\ninterpretations. Also, adding viability assay on ZNF354A-KD upon RSL3 treatment\nwith Lip1/Fer1 rescue is recommended.\nWe have performed some trouble shooting of the BODIPY-C11 staining and\nimproved the signal.\nWe have also performed the experiment suggested by the reviewer, i.e. viability\nZNF354A-KD cells upon RSL3 treatment with Fer1. We did not add it to the\n4\nmanuscript, because we did not fully understand what confirmatory information the\nreviewer was seeking with this experiment.\nFigure legend: U2OS cells siControl or siZNF354A depleted (72 h) were mock-\ntreated or treated with RSL3 (1 μM) for 16 hrs and Ferrostatin (30µM) everyday.\nCell viability was monitored by ATB detection in viable cells using Promega Glo .\nResults are mean ± SD of one representative assay n=36 replicates\n4. There is inconsistency on data presentation. Some data use SEM, while some use\nSD. The authors should clarify in the methods or Figure legends how each is chosen\nor stick to one presentation method.\nWe have now clarified in the methods section and the legends that we use SEM\nwhen we show a representative experiment with multiple similar samples, and SD\nwhen we show data coming from multiple independent experiments.\n5. Line 226, “some 380 of which are…”, it is unclear what is indicated here.\nThis has been rephrased to “of which approximately 380 are”\n6. Line 419, typo in NRF2\nThis has been corrected.\nReply to Reviewer #2\nWe were thrilled to read that the reviewer considers this an exceptional study.\n1. Line 270-272….I am confused, I can see how the phosphomimic KAP1 would\nactivate ZDHHC20L, but how do the authors propose the KAP1 phosphomimic\ncauses ATF2 phosporylation?\nThis is also very intriguing to us and we plan to elucidate this in the future. For the\ncurrent first paper on the topic, we have chosen to remove the phospho-ATF2 blot\nfrom panel 2g, since this information does not contribute to the unrolling of the paper.\n2. Figure 1C, I can’t tell whether the red and purple indicate KAP1 and SETDB1 or\nU2OS and K562? Should Plot the signal or peaks for each protein in each cell type.\nthey were monitored.\n3. Based on the KRABopedia, and limited discussion in the paper, ZNF345a is a\nconserved ancient mammalian KZFP that has at least some conserved activities in\nmice and humans (such as the regulation of ZDHH20L). However there is almost no\ndiscussion that this protein appears to bind several related family members of\nancient mammalian L1s. The authors should provide more analysis of their ChIP-seq\ndata to demonstrate whether the effects on genes are due to the distribution of these\nL1s near target genes. It would also be very interesting to analzye conservation in\nthe gene networks across species ie in mice and humans and whether it can be\nexplained by conservation in the distribution of the L1s and the their target motifs\nIn Supplementary Fig. 3cd, we have now added an analysis on the binding sites of\nZNF354A. Panel c, illustrates that ZNF354A almost exclusively binds to transposable\nelements; panel d shows that these transposable elements are almost exclusively\nLINE-1 elements; Consistently, Suppl. Table 3 shows that among the differentially\nexpressed genes, 78% have a ZNF354A peak within a TE <500 kb of their TSS, and\nof those, 72% are LINE-1 elements. We also mention in the discussion that ZNF354A\nonly appeared in placental mammals, and that analysis of the L1s in mice vs. humans\nwill be of interests to better understand the evolution in the gene networks.\nReviewer #3\nWe thank the reviewer for his/her kind words, it is extremely rewarding to read that a\nreviewer “enjoyed reading” our manuscript and that it “is one of the most cogent\nmanuscripts you have had to review in the past few years”.\nMajor comments:\n1. The only part of the authors logical flow that I find not convincing is the claim that\nATF2 is part of a 'supercomplex' with KAP1 and ZNF354A. Similar 'complexes' of\nKAP1 with multiple transcription factors have been suggested in the past with most\npopular transcription factors (STAT1, p53, and many others) and these models suffer\nfrom first-order interpretation of immunoprecipitation assays against KAP1 and/or\nfirst-order interpretation of results coming from loss of the transcription factor and the\nindirect effects this can have on the cell - this paper does both. Upon careful\nconsideration of the data presented, we cannot exclude that a simpler model could\nbe that ATF2 is bound nearby ZNF354A and therefore an IP for either KAP1 or ATF2\nwill find the other one as they are linked through DNA they bind. In my experience\nDNAse/benzonase treatment are not sufficient to remove this as the transcription\nfactors can protect a small region of DNA. The data presented in figure 2 panel D\nshows that ATF2 presence is necessary for loss of ZNF354A at the protein level,\nwhich is most interesting, but this could be via indirect effects of ATF2-mediated\ntranscription of other targets (genes or non-coding RNAs).\n“could find the other one” just because they are linked to DNA. Re-analyzing our\ndata and performing an additional set of experiments, it appears that part of ATF2 in\nthe IP might indeed be indirect and thus due to DNA. However, some data supports\nthat a sub-pool of ATF2 interacts with ZNF354A-bound KAP1 independently of DNA.\nThis is based on two experiments that were shown in the paper (2d and 6c), and a\nnewly added experiment (Supplementary Fig. 2g).\nFigure 2d: The two first lanes show that phosphorylated endogenous ATF2 co-IPs\nwith KAP1 following aerolysin treatment, while KAP1 is no longer bound to DNA via\nZNF354A. We have now reworded the description of Fig. 2d, raising the issue of\nDNA but mentioning that the results suggest that upon separation of KAP1 from\nZNF354A, it becomes apparent that phosphorylated ATF2 is in a complex with\nKAP1.\nFigure 6c: this experiment confirms the observations of Fig. 2d. Upon H2O2\ntreatment, KAP1 and ATF2 can no longer be co-IPed with ZNF354A. The amount of\nendogenous ATF2 in the KAP1 IP is greatly reduced after H2O2, which could be due\nas the reviewer suggested to the loss of link by DNA. ATF2 is however clearly\ndetectable and again readily detectable with the anti-phospho-ATF2.\nSuppl. Fig. 2g: We performed IPs against three irrelevant KZFPs in comparison to\nZNF354A, and found that only IP of ZNF354A leads to the co-IP of ATF2.\nWe feel that, with the available information, the simplest explanation is that a\nsubpopulation of ATF2 is associated with ZNF354A-bound KAP1, which remains\nbound in its phosphorylated form to KAP1 once the detachment from ZNF354A is\ntriggered.\nThe easiest solution would be for authors either remove all claims of a non-\ncannonical / supercomplex / subcomplex / necessity of direct binding to ATF2 for\nrepression and discuss the above leaving room for interpretation\nWe have eliminated the use of non-canonical complex, supercomplex and\nsubcomplex throughout the text.\nor if they insist on the necessity of providing a model, to provide evidence that ATF2\nis necessary for deposition of H3K9me3 at ZNF354A bound sites (i.e. perform an\nH3K9me3 ChIP-seq assay in cells treated with siRNA targeting ATF2 and show that\nrepression is lost).\nBased on this comment of the reviewer, we have added a sentence in text to\nemphasize that KAP1 and SETDB1 are involved in repressing ZDHHC20L\nexpression, since their silencing is sufficient to trigger expression, in contrast to\nATF2. ATF2 therefore does not appear to be involved in the deposition of H3K9me3\nat ZNF354A bound sites. We propose that a major role of ATF2 is to make the\ncomplex “triggerable”.\nAdditionally, if short timescale data of ZNF354A protein levels following loss of ATF2\nwith a degron system (15-60 minutes) could be obtained the model could be more\nconvincing, as it would be possible to test if ATF2-mediated transcription of other\ntargets is necessary.\nthis approach in the future, targeting either AFT2 or ZNF354A to control the time of\nrelease from DNA loci.\nWe do know that ATF2 has a second role in mediating transcription. Indeed, while\nZDHHC20L expression is triggered by silencing of ZNF354A, this is abolished when\nalso silencing ATF2 (not presented in the manuscript). This might be different pools\nof ATF2, one bound to the KAP1 complex, which is required to trigger disassembly in\na phosphorylation-dependent manner, and a second that acts as a bona fide\ntranscription factor for ZDHHC20L expression.\nAdditionally, if the model is kept and is as presented in panel j of figure 2, authors\nshould explain why ATF2 would not be carried by KAP1 at all KZFP binding sites.\nThis is a key question for the future, as we now mention in the discussion. We\ncurrently have no understanding of this. We plan to perform proteomics and\nsubsequent functional analysis of the complex to start addressing this issue.\nWe have modified the model in panel j of figure 2 to make it more neutral, showing\ninteraction of ATF2 with KAP1 and DNA, and full dissociation of the complex upon\nstress.\nI think removal of this claim would not diminish the value of the manuscript in any\nway as it is tangential to the main discovery.\nWe hope the above answers have addressed the reviewer’s concern.\n2. In most mammalian species ZNF354A has a paralog, ZNF354B, which has almost\nthe same zinc finger array and is therefore expected to bind most if not all of the\nsame targets. Most importantly, ZNF354B has very high expression levels in most\ncell types. The authors should discuss this and provide future plans to study both\nindependently. Most importantly, they should also provide information and/or\nexperiments to prove that their siRNA against ZNF354A is not also targeting\nZNF354B - the same for other reagents if relevant. If reagents are found to target\nboth, I think it would be acceptable to discuss them as paralogs that can provide\nredundancy and I don't think studying both independently is absolutely necessary for\nthis first manuscript on the topic\nWe thank the reviewer for this interesting suggestion. We now mention that cells\nexpress ZFN354B, which shares 86% sequence identity with ZNF354A. The two\nproteins are indeed almost identical with regards to the KAP1 binding domain and\nthe zinc fingers but differ significantly in the linker, also the phosphorilation site Ser-\n169 is not present in ZNF354B (Suppl. Fig. 2d).\nWe performed qPCR analysis for ZNF354B and found that it was not affected by the\nsilencing of ZNF354A (Suppl. Fig. 2e).\nWe also tested the effect of silencing ZNF354B using 3 different siRNAs and found\nthat they did not lead to ZDHHC20L expression (Suppl. Fig. 2f). This finding is\nconsistent with the data in Krabopedia, which indicates that ZNF354B binds much\nfewer DNA loci than ZNF354B (Suppl. Fig. 3e).\n3. The authors don't discuss the binding of ZNF354A versus transposable elements\nanywhere in the manuscript - I find this surprising since the Trono lab is co-author on\n8\nthe manuscript - according to Krabopedia it is enriched in mammalian-conserved L1\nelements, as is ZNF354B. The manuscript should at least mention this and provide\nan analysis (maybe in supplemental) of the status (transposable element or not?) of\nthe most important binding sites identified. This would enrich the finding with context\nabout evolution of the gene regulatory network that is proposed.\nA similar point was raised by reviewer 2. We have now added an analysis on the\nbinding sites of ZNF354A (Suppl. Fig. 3cd): Panel c, illustrates that ZNF354A almost\nexclusively binds to transposable elements; panel d shows that these transposable\nelements are almost exclusively LINE-1 elements; and Suppl. Table 3, which list 100\ngenes found in the RNA-seq analysis of ZNF354 KD cells are involved in anti-oxidant\nresponse, shows that the ZNF354A binding regions in the vicinity of these genes\ninclude LINE-1 elements. We also mention that ZNF354A only appeared in placental\nmammals, and that analysis of the L1s in mice vs. humans will be of interests to\nbetter understand the evolution of the gene network.\n4. The term 'master regulator' is overused - if anything in your model ATF2, and not\nZNF354A, is the master regulator, as it activates the targets in the networks and is\nnecessary for loss of ZNF354A-mediated repression.\nWe agree that master regulator is an overused term and have removed it. AFT2\nindeed controls the loss of ZNF354A-mediated repression and thus plays a key role,\nwhile ZNF354A determines which genes are repressed.\n5. Discuss future experiments performing an RNA-seq in aerolysin-treated cells\nwithout ZNF354A and following short term dynamics of induction of the network,\nalong with a timecourse of loss of H3K9me3 at these sites upon stress to test the\nhypothesis that repression is there to prevent a rapid response, but allow for a\ndelayed one.\nWe agree that the hypothesis that “repression is there to prevent a rapid response,\nbut allow for a delayed one” is particularly intriguing. We now highlight this idea in\nthe Discussion as an exciting direction for future research. Indeed, combining RNA-\nseq with a time-course analysis of H3K9me3 dynamics at target sites upon pathway\nstimulation would be a powerful approach to test this model. We thank the reviewer\nfor this insightful suggestion.\nMinor comments:\nPlease change all instances of KAP1 to TRIM28 as it is the officially recognized\nname\nWe acknowledge that TRIM28 is the official gene name. However, the protein\nappears to most commonly be referred to as KAP1 in the epigenetics and chromatin\nbiology literature. To maintain consistency with the field and ensure clarity for our\nintended audience, we propose to retain the name KAP1 throughout the manuscript.\nAs noted in the introduction, we clearly state that KAP1 refers to TRIM28. Of course,\nwe are happy to switch to TRIM28 should the reviewer or journal prefer strict\nadherence to official nomenclature.\n9\nline 29 - \"It is epigenetically repressed, by a complex comprising\" - the comma is\nunnecessary\nThis has been corrected.\nFigure 1 - improve annotation of gene track panels in the manuscript, it is unclear at\nfirst sight where the long isoform starts from, especially when viewing the figure not\nfully zoomed in\nFigure 1 has been improved to address the concern that was raised.\nline 167 - \"Active promoter marks, H3K27Ac and H3K4me3, were found, flanking\nthese repressive regions\" - these commas are not necessary\nThis has been corrected.\nline 237 - \"The specificity for ZNF354A was further established by\nimmunoprecipitation (IP) experiments against KAP1 using U2OS cells\noverexpressing irrelevant KZFPs.\" - rephrase to 'overexpressing ZNF354A or two\nother irrelevant KZFPs as controls'\nThe sentence was rephrased.\nlayout of figure 2 is hard to follow between panels - consider having panel d in place\nof e, and present e on a line below as an horizontal instead of vertical panel\nFigure 2 has been reorganized to ease its reading.\nline 390 - please calculate enrichment of presence near upregulated genes to test if\nmore than expected by chance. Also provide clarity in the directionality of\ndifferentially regulated genes\nThe comment of the reviewer highlighted that the sentence that was previously on\nline 390 was somewhat misleading.\nIt has been rewritten and now reads as follow:\nTo identify genes that reside in the vicinity of the 1,665 ZNF354A peaks (Imbeault et\nal, 2017), we made use of our ChIP-seq data from HEK293T cells overexpressing\nHA-tagged ZNF354A, and searched for genes harboring their TSS within 300 kb,\nchosen as a cut-off. We identified 2,116 genes potentially regulated by ZNF354A.\nIn the discussion section, add a sentence or two on the pattern of expression of\nZNF354A and what that could mean for regulation of the gene network it controls if\ncells express it or not.\nWe now mention in the discussion that ZNF354A is expressed rather ubiquitously, as\ndocumented in GTEX Portal, with notably low expression in the liver –consistent with\nour previous observation that liver derived HepG2 cells constitutively express\nZDHHC20L– and high expression in the kidney where ZNF354A was first\ndocumented and called Kid-1. We also now speculate on the consequences of the\nZNF354A expression levels in these two tissues.\nFigure 4A - the color legend for the p-value scale should be rescaled to something\nmeaningful\nWe believe the reviewer refers to Fig. 4c. We now have removed the colors and\nadded individual p values. Thank you for picking this up.\n10"}, {"round": 2, "reviewer_comments": {"reviewer_1": "The authors have properly addressed the concerns raised by this referee. Publication in Nature Communications is recommended.", "reviewer_2": "The author's have addressed my concerns. Exciting paper.", "reviewer_3": "I am satisfied with the changes and in my view the manuscript is ready for publication.", "reviewer_4": "I co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part of the Nature Communications initiative to facilitate training in peer review and to provide appropriate recognition for Early Career Researchers who co-review manuscripts."}, "author_response": ""}]

Decision letter