MESH1 knockdown triggers proliferation arrest through TAZ repression

Sun, Tianai; Ding, Chien-Kuang Cornelia; Zhang, Yuning; Zhang, Yang; Lin, Chao-Chieh; Wu, Jianli; Setayeshpour, Yasaman; Coggins, Si’Ana; Shepard, Caitlin; Macias, Everardo; Kim, Baek; Zhou, Pei; Gordân, Raluca; Chi, Jen-Tsan

doi:10.1038/s41419-022-04663-6

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Published: 10 March 2022

MESH1 knockdown triggers proliferation arrest through TAZ repression

Tianai Sun ORCID: orcid.org/0000-0001-6668-4220^1,2^na1,
Chien-Kuang Cornelia Ding^1,2^na1,
Yuning Zhang^2,3,
Yang Zhang^1,2,
Chao-Chieh Lin ORCID: orcid.org/0000-0001-5890-9004^1,2,
Jianli Wu^1,2,
Yasaman Setayeshpour^1,2,
Si’Ana Coggins⁴,
Caitlin Shepard⁴,
Everardo Macias⁵,
Baek Kim⁴,
Pei Zhou ORCID: orcid.org/0000-0002-7823-3416⁶,
Raluca Gordân^1,2,7,8 &
…
Jen-Tsan Chi ORCID: orcid.org/0000-0003-3433-903X^1,2,3

Cell Death & Disease volume 13, Article number: 221 (2022) Cite this article

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Abstract

All organisms are constantly exposed to various stresses, necessitating adaptive strategies for survival. In bacteria, the main stress-coping mechanism is the stringent response triggered by the accumulation of “alarmone” (p)ppGpp to arrest proliferation and reprogram transcriptome. While mammalian genomes encode MESH1—the homolog of the (p)ppGpp hydrolase SpoT, current knowledge about its function remains limited. We found MESH1 expression tended to be higher in tumors and associated with poor patient outcomes. Consistently, MESH1 knockdown robustly inhibited proliferation, depleted dNTPs, reduced tumor sphere formation, and retarded xenograft growth. These antitumor phenotypes associated with MESH1 knockdown were accompanied by a significantly altered transcriptome, including the repressed expression of TAZ, a HIPPO coactivator, and proliferative gene. Importantly, TAZ restoration mitigated many anti-growth phenotypes of MESH1 knockdown, including proliferation arrest, reduced sphere formation, tumor growth inhibition, dNTP depletion, and transcriptional changes. Furthermore, TAZ repression was associated with the histone hypo-acetylation at TAZ regulatory loci due to the induction of epigenetic repressors HDAC5 and AHRR. Together, MESH1 knockdown in human cells altered the genome-wide transcriptional patterns and arrested proliferation that mimicked the bacterial stringent response through the epigenetic repression of TAZ expression.

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Introduction

All organisms are constantly exposed to a wide variety of environmental stresses. For example, most solid tumor cells experience hypoxia [1, 2], lactic acidosis [3, 4], and nutrient deprivations [5,6,7,8,9], necessitating stress responses to ensure survival and homeostasis. In bacteria, the main stress mechanism is “stringent response” mediated by elevated alarmone (p)ppGpp via synthesis by its synthetase (RelA), or inhibited degradation by its hydrolase (SpoT). The accumulated (p)ppGpp triggers transcriptional reprogramming and proliferation arrest [10] through suppression of de novo dNTP synthesis [11, 12]. While a similar stress response has not been reported in metazoan, metazoan genomes encode MESH1 (Metazoan SpoT Homolog 1, also named HDDC3). The difficulties are embedded in the fact that neither (p)ppGpp nor RelA exists in metazoan cells. A previous study [13] described the conserved structures of Drosophila and human MESH1 and their in vitro enzymatic activities to degrade (p)ppGpp. Genetic depletion of Drosophila MESH1 enhanced stress survival and triggered transcriptional responses bearing significant similarities to bacterial stringent response [13]. Recently, we have shown that MESH1 is a cytosolic NADPH phosphatase and MESH1 knockdown protected cancer cells against ferroptosis [14] and triggered integrative stresses response. However, much remains unknown about the phenotypic responses to MESH1 knockdown.

Here, we report that MESH1 knockdown robustly arrests proliferation, depletes dNTP, inhibits tumor spheres, and xenograft growth. Mechanistically, these anti-growth effects are mediated by the transcriptional repression of HIPPO effector TAZ (encoded by WWTR1, WW domain containing transcription regulator 1), known to regulate proliferation and tumorigenesis. In addition, the transcriptional repression of TAZ is associated with a repressive chromatin modulation by the induction of HDAC5 (histone deacetylase 5) and AHRR (aryl-hydrocarbon receptor repressor). The regulation of HDAC5, AHRR, TAZ, and cell proliferation depends on the enzymatic activities of MESH1. Together, our results indicate that MESH1 knockdown in human cells triggers proliferation arrest through epigenetically repressing TAZ transcription, and may hold antitumor therapeutic potential.

Results

MESH1 knockdown reduced cell number, proliferation, and tumor growth

The polymorphism in the 3′UTR of MESH1 was found associated with a risk of breast cancers, implying its relevance to tumor biology [15]. Interestingly, TCGA datasets revealed that MESH1 was generally expressed at higher levels in tumor than non-tumor tissues (Supplementary Fig. 1a). Therefore, we investigated the phenotypic response of cancer cells to MESH1 knockdown by multiple siRNAs (Supplementary Fig. 1b, c). MESH1 knockdown significantly reduced the cell number of non-small cell lung cancer (H1975) (Fig. 1a) under different serum levels tested by crystal violet staining. We expanded this finding in a broader panel of cancer cell lines, including renal cell carcinoma (RCC4, 786-O), breast cancer (BT20, BT474, MCF-7), chondrosarcoma (SW-1353), and fibrosarcoma (HT-1080), and noticed a consistent cell number reduction by MESH1 knockdown (Supplementary Fig. 1d). The antitumor effects of MESH1 knockdown in H1975, RCC4, and 293 T were further confirmed using CellTiter-Glo assay (Supplementary Fig. 1e). In essence, the effects were specific since they were abolished by the reexpression of the wild-type MESH1 (Supplementary Fig. 1f). Interestingly, the enzymatic dead mutant MESH1 did not restore the cell number (Supplementary Fig. 1f). And the knockdown of NAD(H) kinase (NADK), mediating the NADPH generation opposite to MESH1’s activity, largely mitigated the reduced cell growth (Supplemental Fig. 1g). These findings indicated the importance of MESH1 NADPH phosphatase activity in regulating cell growth. We further validated that MESH1 knockdown by doxycycline (Doxy)-inducible shRNAs (Supplementary Fig. 1h, i) also triggered growth inhibition tested by cell counting (Fig. 1b) and the Incucyte^® S3 over time (Fig. 1c and Video 1a–c). Importantly, upon the Doxy withdrawal and restoration of MESH1 expression, cell growth resumed (Fig. 1d). Reciprocally, wild-type MESH1 expression enhanced proliferation, while the effect of the enzymatic dead mutant MESH1 was much reduced (Fig. 1e).

**Fig. 1: *MESH1* knockdown led to cell proliferation arrests and delayed xenograft growth.**

Next, we tested the anti-growth effects of MESH1 removal in 3D tumor spheres and xenografts. The doxycycline-induced MESH1 knockdown significantly reduced the number and size of tumor spheres (Fig. 1f). We then dissipated primary spheres and seeded the same number of cells for the secondary assays, which further confirmed the continuous suppression of the tumor sphere formation by MESH1 knockdown (Fig. 1g). Similar results were obtained in vivo using subcutaneous H1975 xenografts. The induction of two MESH1 shRNAs significantly reduced the volume and weight of tumors (Fig. 1h). Collectively, inducible MESH1 knockdown inhibited tumor growth both in vitro and in vivo.

Mechanistically, we investigated whether MESH1 knockdown (1) inhibited cell proliferation (BrdU incorporation assay), or (2) enhanced cell death (CellTox Green assay) to reduce cell number. MESH1 knockdown significantly reduced the BrdU incorporation (proliferation) (Fig. 1i) but did not increase cell death (Supplementary Fig. 1j). Additionally, the propidium iodide (PI) stain suggested that MESH1 knockdown inhibited the G1-S phase transition (Fig. 1j) without increasing the sub-G1 population, supporting the lack of significant cell death. Collectively, MESH1 knockdown inhibited cell proliferation to achieve anti-growth effects.

The prognostic significance of MESH1 in tumor expression datasets

Based on the antitumor phenotypes associated with MESH1 knockdown, we analyzed the prognostic significance of MESH1 (HDDC3) expression in the tumor datasets. Results suggested that lower MESH1 mRNA expression was associated with significantly better survivals in patients with renal cell carcinoma (RCC) (Supplementary Fig. 2a), clear cell type RCC (TCGA) (Supplementary Fig. 2b), lung cancers (Supplementary Fig. 2c, d) [16], neuroblastoma (GSE62564) (Supplementary Fig. 2e), colon cancer (GSE38832) [17] (Supplementary Fig. 2f), meningioma (GSE16581) [18] (Supplementary Fig. 2g), and follicular lymphoma (GSE16131) [19] (Supplementary Fig. 2h). These in vivo associations of low MESH1 levels and better clinical outcomes suggested a functional role of MESH1 in tumor biology.

Transcriptional responses and dNTP depletion upon MESH1 knockdown

One prominent feature of bacterial stringent response is transcriptional reprogramming [10, 20]. MESH1 removal in Drosophila downregulated the DNA and protein synthesis-related gene expression [13]. Therefore, we analyzed the global transcriptional responses to MESH1 knockdown (Fig. 2a) in H1975 cells. 994 genes were selected based on the filtering criteria of at least seven observations with absolute log₂ values >0.47, and arranged by clustering (Fig. 2a) and the differentially expressed genes were shown in Table 1. Gene Set Enrichment Analysis (GSEA) indicated that MESH1 knockdown inhibited multiple cell cycle progression-related pathways (Fig. 2b), including repressing the expression of CDC6 (cell division cycle 6), and CDK1 (cyclin-dependent kinase 1) (Fig. 2a), consistent with the proliferation arrest phenotypes (Fig. 1). MESH1 knockdown also induced the expression of HDAC5 and HDAC9 (histone deacetylases), implicating epigenetic modulations. Additionally, MESH1 knockdown repressed the expression of RRM1 (ribonucleotide reductase M1) and RRM2 (Fig. 2c), two subunits of ribonucleotide reductase (RNR) responsible for de novo synthesis of dNTPs [21, 22]. As ppGpp depletes dNTPs in bacteria [12], we measured the dNTP levels in H1975 and RCC4 (Fig. 2d) and found that MESH1 knockdown largely reduced the levels of all four dNTPs. Together, these results suggested that MESH1 knockdown depleted dNTPs and repressed the expression of genes regulating dNTP synthesis and cell cycle progression.

**Fig. 2: The transcriptional response to *MESH1* knockdown.**

Table 1 The list of differentially expressed genes upon MESH1 knockdown.

Full size table

MESH1 knockdown repressed TAZ mRNA expression that contributed to the antitumor phenotypes

Interestingly, we noted consistent repression of WWTR1 (WW domain containing transcription regulator, which encodes TAZ (transcriptional coactivator with the PDZ-binding motif) (Fig. 2a). TAZ and its paralog YAP (Yes-associated protein) are well-recognized HIPPO effectors that regulate proliferation and self-renewal of cancer cells [23, 24]. While YAP/TAZ are conventionally co-regulated by protein phosphorylation, and translocation [23, 24], MESH1 knockdown reduced TAZ mRNA level in all tested cancer cells (Fig. 2e, f and Supplementary Fig. 3a). Importantly, wild-type, but not mutant, MESH1 restoration mitigated TAZ repression, showing the specificity (Supplementary Fig. 3b). The rescue by NADK knockdown further reiterated the importance of MESH1 enzymatic activity (Supplementary Fig. 3c). While TAZ levels are affected by cell density at the posttranslational level [25,26,27,28], we found that MESH1 knockdown reduced TAZ mRNA to comparable degrees in H1975 and RCC4 grown with low, medium, or high cell density (Supplementary Fig. 3d). Similarly, MESH1 knockdown did not alter the nuclear/cytosolic distribution of TAZ measured by fractionation/Western blots (Supplementary Fig. 3e) and immunofluorescence (Supplementary Fig. 3f). Consistently, GSEA analysis indicated that TAZ-, but not YAP-, regulated pathways [29] were significantly depleted upon MESH1 knockdown in H1975 (Supplementary Fig. 3g). In the five indicated tumor datasets, tumors with low MESH1 expression levels also displayed low TAZ expression (Supplementary Fig. 3h), consistent with the regulatory relationships established in cultured cells. However, such a relationship was not found in other tumor datasets, which may be due to the various confounding environmental factors. Collectively, these data indicated that MESH1 knockdown specifically repressed TAZ mRNA and pathway activity by a noncanonical mechanism.

Next, the contribution of TAZ repression to various phenotypic alterations of MESH1 knockdown was investigated by restoring the constitutively active TAZS89A [15, 30] (Supplementary Figs. 4a, 5a). TAZ restoration significantly rescued the reduced cell number (Supplementary Fig. 4b) and BrdU incorporation (Fig. 3a) upon MESH1 knockdown. In contrast, TAZ depletion completely ablated the stimulation of cell growth by MESH1 overexpression (Fig. 3b). Consistently, TAZS89A expression partially rescued the dNTP depletion (Fig. 3c) and cell cycle arrest by MESH1 knockdown (Fig. 3d, e; gating strategy shown in Supplementary Fig. 4c).

**Fig. 3: *TAZ* repression contributed significantly to the proliferation arrests of *MESH1* knockdown in H1975 cells.**

TAZ is known to regulate the self-renewal capacity of cancer cells and tumor growth [23]. Indeed, TAZS89A increased the number of spheres by ~92 folds in the shMESH1 groups, whereas only ~2 folds in the control (Fig. 3f, g), a trend persisted in the secondary sphere formation assay (Supplementary Fig. 5b). Furthermore, the limiting dilution assay showed that MESH1 knockdown massively reduced the stem cell frequency from 1/63 to 1/1869 in H1975, and was partially restored by TAZS89A expression to 1/112 (Fig. 3h). Next, we tested the potential of TAZ restoration in mitigating the tumor inhibition effects of MESH1 knockdown in xenografts. We found that the in vivo expression of TAZS89A in the MESH1-removed xenografts rescued the tumor volume and weight by ~3 folds (Fig. 3i and Supplementary Fig. 5c). Collectively, these data indicated the importance of TAZ repression to the dNTP depletion, proliferation arrest, reduced sphere formation, and tumor growth inhibition phenotypes associated with MESH1 knockdown. However, TAZ restoration only partially reversed these antitumor phenotypes of MESH1 removal, indicating that TAZ repression may not be the only factor that contributed.

TAZ downregulation contributed to the transcriptional changes of MESH1 knockdown

As TAZ functions as a transcription coactivator, we determined the role of TAZ repression in regulating the transcriptional responses to MESH1 knockdown (Fig. 4) by comparing the MESH1-knockdown gene signatures between the control and TAZS89A-transfected groups (Fig. 4a). While the transcriptional responses were similar, TAZ restoration mitigated the MESH1 knockdown-affected changes in ~33% (258 out of 786 genes) of both the repressed (123 of 434 genes) and induced genes (135 of 352 genes) (Fig. 4b), and the rescued gene lists were included in Table 2. Interestingly, the MESH1-affected genes restored by TAZ expression included several known cell cycle-related genes, such as CDC6, CDK1, RRM1, RRM2 (Fig. 4c), CCNE2 (Cyclin E2), KLF2 (Kruppel-like factor 2), and KLF4 (Kruppel-like factor 4) [25, 31, 32]. ChIP-qPCR further showed the binding of TAZ to the regulatory regions of CDC6 and RRM2 (Fig. 4d) as a transcriptional effector. Overall, these results indicated that TAZ repression mediated ~1/3 of the transcriptional response to MESH1 knockdown, including the downregulation of many cell cycle-related genes that contributed to the anti-growth effects (Fig. 3).

**Fig. 4: The contribution of *TAZ* repression to the transcriptional responses of *MESH1* knockdown in H1975 cells.**

Table 2 The list of MESH1-affected genes which was rescued by the expression of TAZS89A.

Full size table

Next, we investigated the epigenetic modulations on TAZ measuring H3K27ac (canonical active enhancer mark) levels at TAZ promoter/enhancer regions annotated by the GeneHancer [33] (Supplementary Fig. 6a). MESH1 knockdown significantly reduced the abundance of H3K27Ac at two separate loci at the promoter/enhancer region 2 of TAZ (Fig. 4e), suggesting a closed structure of the TAZ chromatin. Comparatively, H3K27Ac at the YAP promoter or the heterochromatin region was not significantly affected. Furthermore, NADK knockdown reversed the histone hypo-acetylation at TAZ promoter/enhancer region 2 (Supplementary Fig. 6b), implicating a key role of MESH1 enzymatic activity in employing its epigenetic modulation on TAZ. Importantly, epigenetic activation of TAZ by the CRISPR activation (CRISPRa) (Supplementary Fig. 6c), which recruited a transcriptional activation domain by two individual sgRNAs (designed by the SAM Cas9 activator design tool [34]) to TAZ promoter/enhancer region 2, also rescued the repressed expression of several TAZ target genes (Supplementary Fig. 6d, e). Finally, TAZ re-activation significantly mitigated the proliferation arrest (Supplemental Fig. 6f) upon MESH1 knockdown. Altogether, these data revealed the critical role of TAZ epigenetic repression in inhibiting TAZ downstream gene expression and proliferation phenotypes of MESH1 knockdown.

Histone deacetylases (HDACs) are known to reduce histone acetylation and form inhibitory complexes to repress gene expression [35]. Interestingly, MESH1 knockdown induced HDAC5 and HDAC9 expression (Supplementary Fig. 7a, b), which might contribute to the TAZ repression. Indeed, the pan-HDAC inhibitor (Trichostatin A or TSA) reversed TAZ repression upon MESH1 knockdown (Fig. 4f). To identify the specific HDAC(s) involved in TAZ regulation, we knocked down HDAC1, 2, 3, 5, and 9 individually and measured their effects on TAZ repression upon MESH1 knockdown. Among all tested HDACs, only HDAC5 knockdown rescued TAZ repression (Fig. 4g), consistent with the rescued effect of the HDAC5-specific inhibitor LMK235 (Fig. 4h). Since HDAC5 activity can be regulated by nuclear translocation [36], we fractionalized the nucleus vs. cytosol and found that MESH1 knockdown also dramatically increased the nuclear fraction (putative transcriptionally active) of HDAC5 (Fig. 4i). Together, these data indicated that the increased levels and activities of HDAC5 by MESH1 knockdown contributed to the TAZ repression.

HDAC5 and AHRR formed a repressing complex to inhibit TAZ transcription

Here, we aim to identify the HDAC5-interacting transcription factor(s) that regulates TAZ expression. Toward this goal, we compared the list of 48 published HDAC5 interactors (BioGRID database: [37]) with all eight top documented TAZ-binding transcription factors (QIAGEN CLC Genomics Workbench [38]). Such a comparison identified AHRR (aryl-hydrocarbon receptor repressor) and AHR (aryl-hydrocarbon receptor) as potential candidates. AHRR was induced by MESH1 knockdown (Supplementary Fig. 7c) and reported to be associated with HDAC5 as a repressing complex component [39] that competes with and inhibits the function of AHR [39]. AHR is predicted to target the regulatory regions of TAZ by QIAGEN CLC Genomics Workbench [38]. Therefore, we sought to determine the potential of AHRR and AHR in the regulation of TAZ by MESH1.

First, we confirmed that the restoration of wild-type, but not mutant, MESH1 abolished HDAC5 and AHRR induction (Supplementary Fig. 7d). Next, co-knockdown of NADK and MESH1 also diminished the induction of HDAC5 and AHRR (Supplementary Fig. 7e), suggesting the relevance of MESH1’s enzymatic activity. Second, we validated the interaction between HDAC5 and AHRR by co-immunoprecipitation in H1975 cells transfected with HA-tagged AHRR and Flag-tagged HDAC5 (Fig. 5a). Third, AHRR knockdown (Supplementary Fig. 7c) substantially rescued TAZ repression by MESH1 knockdown (Fig. 5b). Consistently, the knockdown of either HDAC5 or AHRR increased the expression of CDK1, CDK6, RRM1, and RRM2 (Fig. 5c) and the cell number (Fig. 5d). Overall, these data indicated that MESHI1 knockdown upregulated HDAC5 and AHRR, forming a repressing complex, to inhibit the expression of TAZ and its target genes, leading to the proliferation arrest.

**Fig. 5: The effect of HDAC5 and AHRR as epigenetic co-repressors on *TAZ* downregulation and cell proliferation arrest in H1975.**

Since AHR has been reported to bind at TAZ regulatory regions and promote TAZ transcription [26, 29], we investigated the potential that HDAC5 and AHRR could repress TAZ expression by inhibiting the binding of AHR to TAZ regulatory regions. The canonical AHR-responsive element (AHRE) contains the core sequence 5′-GCGTG-3′. Among the predicted AHRE sites in the five TAZ promoter/enhancer regions (Fig. 5e, annotated by the GeneHancer [33]), two were validated by ChIP-qPCR (Fig. 5f). More importantly, MESH1 knockdown reduced the AHR occupancy at TAZ regulatory regions (Fig. 5f), consistent with the TAZ repression. Furthermore, AHR knockdown (Supplementary Fig. 7g), similar to MESH1 knockdown, repressed TAZ (Fig. 5g) and proliferative gene expression (Fig. 5h) and inhibited cell proliferation (Fig. 5i) and tumor growth in vivo (Fig. 5j and Supplementary Fig. 7h, i). Importantly, tumors in the indicated four datasets with lower MESH1 expression have higher levels of HDAC5 (Supplementary Fig. 7j) in patients. In the tumor RNA-seq dataset that contained AHRR expression levels, tumors with low MESH1 expression also displayed a high level of AHRR (Supplementary Fig. 7k). Altogether, the abovementioned evidence supported the idea that HDAC5 and AHRR upregulation upon MESH1 knockdown mediated the proliferation arrest phenotypes by reducing AHR binding and TAZ transcription. In conclusion, we proposed a model by which MESH1 knockdown exerts antitumor effects through repressing TAZ mRNA expression via an epigenetic modulation achieved by HDAC5-AHRR upregulation (Supplementary Fig. 8).

Discussion

While metazoan genomes encode MESH1, the homolog of bacterial SpoT, our understanding of its functional role remains limited. Here, we have shown that MESH1 knockdown triggered reproducible proliferation arrest and altered transcriptional patterns that mimicked the reduced proliferation phenotype of bacterial stringent response. First, the cell cycle arrest was associated with the repression of cell cycle gene expression, similar to the transcriptional feature of the stringent response [20]. Second, MESH1 knockdown depleted dNTPs, reminiscent of the bacterial ppGpp-mediated dNTP depletion [11, 12]. However, MESH1 knockdown also carried some distinct phenotypes, including TAZ repression via epigenetic modulations mediated by the induction of HDAC5/AHRR repressor complex. Therefore, our studies presented an interesting example in which the same protein homologs mediated similar phenotypes in different organisms via re-wiring through distinct substrates and mechanisms.

The Hippo signaling pathway exerts profound effects on cellular proliferation, survival, cell death, and organ sizes [25,26,27,28, 40, 41]. YAP and TAZ, two Hippo effectors, are usually tightly co-regulated by the phosphorylation of the kinase cascade of MST1/2, LATS1/2, and RASSF family proteins. Hence, our findings discovered a novel and interesting features. First, only TAZ, but not YAP, was affected by MESH1 silencing. In fact, the YAP level was slightly increased, which might reflect a negative feedback loop of HIPPO activity noted in previous studies [42, 43]. Second, TAZ repression occurred at the mRNA instead of the posttranslational level. Previously, ETS (E26 transformation-specific) and MRTF/SRF have been reported to be involved in the transcriptional activation of TAZ mRNA [44, 45]. These results implied that MESH1 was also required to maintain the TAZ mRNA expression, the activity of the HIPPO pathway, and thus cellular proliferation. Interestingly, many components of the HIPPO pathway (including YAP and TAZ) first emerge in cnidarians, a very ancient group of metazoans [46]. All major domains of YAP and TAZ are also conserved between cnidarians and mammals. Given that MESH1 also shares the conserved domains with the bacterial hydrolase SpoT, it is tempting to speculate the functional convergence between MESH1 and the HIPPO pathway as they both appear in metazoans during evolution.

MESH1 was a cytosolic NADPH phosphatase [14]. Here, we discovered that the enzymatic activity is essential for the HDAC5-AHRR upregulation, TAZ repression, and antitumor effects. However, the underlying mechanisms are still unknown. In the future, it will be critical to investigate the connection between NADPH and transcriptional control of the epigenetic repressing complex. Furthermore, in bacteria, different environmental stresses (i.e., amino acid deprivation, heat shock, iron deficiency, etc.) trigger the ppGpp accumulation. While MESH1 depletion leads to a stringent-like stress response, it is unclear which external stimuli activate the stringent response in metazoan, which requires further investigation. Despite these knowledge gaps, supported by the extensive amount of data, we demonstrated that MESH1 inhibition potentially represented a novel anti-growth response in cancer cells with significant therapeutic potentials. We can take advantage of the evolutionarily conserved pathways, proteins, and metabolites as well as the available X-ray structures of MESH1 [13, 14], to design MESH1 inhibitors and repress tumor proliferation as novel therapeutics.

Materials and methods

MESH1-knockdown using RNAi and shRNAs

Nontargeting siRNA (siNT) was purchased from Qiagen (AllStars Negative Control siRNA, SI03650318). MESH1 targeted siRNAs were purchased from: Dharmacon: siMESH1-1 (target sequence GGGAAUCACUGACAUUGUG, D-031786-01); siMESH1-3 (target sequence GGACAGGAUUCAUACGCCA, J-031786-10); siNADK (target sequence UGAAUGAGGUGGUGAUUGA, CGCCAGCGAUGAAAGCUUU, GAAGACGGCGUGCACAAU, CCAAUCAGAUAGACUUCAU, M-006318-01) Qiagen: siMESH1-2 (target sequence CTGAAGGTCTCCTGCTAACTA, SI04167002). For transient knockdown, 60 pmole of siRNA and 9 μL of Lipofectamine RNAiMAX (ThermoFisher Scientific, #13778150) were reverse transfected together with 300 μL of opti-MEM (Gibco, #11058-021) to 2 × 10⁵ cells for 48–72 h. Empty vector for shRNA (empty) was purchased from Addgene (pLKO.1 puro, #8453). MESH1 targeted shRNAs were purchased from Sigma: shMESH1-1 (target sequence TGAGGTGGAGCTACACTTTGG, TRCN0000243216), shMESH1-2 (target sequence TGGTGGAGGAGGTAACAGATG, and TRCN0000243217), shMESH1-3 (target sequence TCCATCCTTCCCAGATATTAG and TRCN0000243218). AHR targeted dox-inducible shRNAs were purchased from Horizon Discovery: shAHR-1 (ID: V3SH11252-227709444), shAHR-2 (ID: V3SH11252-230006145). For lentivirus package, 2 × 10⁶ HEK-293T cells were transfected with 4 μg of psPAX2 (Addgene, #12260), 0.4 μg of pMD2.G (Addgene, #12259), 4 μg of plasmid (empty or shRNAs), 24 μL of TransIT-LT1 (Mirus, MIR2305), and 800 μL of opti-MEM together with culture media for 48 h until the supernatant collection (virus soup). For stable shRNA overexpression, 10⁵ cells were infected with 500 μL of the virus soup together with 8 μg/mL polybrene for 24 h followed by the puromycin (1 μg/mL) selection continuously, and single-cell clones were generated after the selection until the validation of its overexpression on the western blot. For inducible shRNA knockdown, 2 μg/mL doxycycline was added to the culture media for at least 48 h before cell lysate collection or further dissipation in the tumor sphere formation assay (doxycycline was continuously added).

TAZS89A and MESH1 overexpression

Lentiviral or retroviral plasmids were purchased from Addgene: empty (pBABE-puro, #1764); TAZS89A (pLenti-EF-FH-TAZS89A-ires-blast, #52084) [47]. MESH1-WT and MESH1-mutant (MESH1 E65A) was generated using the lentiviral backbone plasmid pLX302 (Addgene #25896).

Cell culture

RCC4, HEK-293T, H1975, BT20, BT474, 786 O, SW-1353, MCF-7, and HT10801 were purchased from the Duke Cell Culture Facility and tested negative for mycoplasma. All cells except for the tumor sphere formation assay were cultured in the normal media: DMEM (ThermoFisher Scientific, 11995-DMEM,) 10% heat-inactivated fetal bovine serum (Hyclone #SH30070.03HI) and 1% pen-strep (ThermoFisher Scientific, #15140122) in a humidified incubator, at 37 °C with 5% CO₂. For the tumor sphere formation, cells were cultured in the CCSC media: DMEM:F12 with l-glutamine (Invitrogen, #11330-032), 1% pen-strep (ThermoFisher Scientific, #15140122), 0.2x B27 supplement (Invitrogen, #17504044), 4 μg/mL heparin (Sigma, #H3149-50ku), 1x nonessential amino acid (Hyclone, #SH3023801), 1x sodium pyruvate (ThermoFisher Scientific, #11360-070), 40 ng/mL human EGF (R&D systems, #236-EG), 20 ng/mL bFGF (Invitrogen, #PHG0024), and 1 mL/100 mL N2 supplement (Invitrogen, #17502048).

Western blot

Cell lysates were collected in the RIPA buffer (Sigma, R0278) with protease inhibitors (Roche, 11836170001) and protein concentrations were measured with BCA assay. For Western blots, 15–30 μg of protein were loaded on 8–15% SDS-PAGE gels, semi-dry transferred to the PDVF membrane, blocked with 5% milk in TBST, and then blotted with antibodies at 4 °C overnight. Antibodies were purchased from the anti-MESH1 antibody (Proteintech, 21091-1-AP); anti-β-tubulin antibody (Cell Signaling Technology, #2128); anti-YAP/TAZ antibody (Cell Signaling Technology, #8418); Anti-GAPDH antibody (Santa Cruz, sc-25778); anti-H3K27Ac antibody (Cell Signaling Technology, #8173); anti-mouse-IgG HRP (Cell Signaling Technology, #7076); and anti-rabbit-IgG HRP (Cell Signaling Technology, #7074). All primary antibodies were diluted 1:1000 in 5% BSA and secondary antibodies (anti-mouse-IgG HRP and anti-rabbit-IgG HRP) were diluted 1:2000 in 5% milk. Blots were developed with SuperSignal West Pico PLUS Chemiluminescent Substrate (ThermoFisher, #34577) and exposed in the ChemiDoc imaging system (Biorad). Each western blot image was repeated for three biologically independent times with similar trends.

Quantitative real-time PCR

RNA was extracted with the RNeasy mini kit (Qiagen, #74104), reverse transcribed by the SuperScript II (ThermoFisher Scientific, #18064014) to generate cDNAs for qRT-PCR using primers and the Power SYBRGreen Mix (ThermoFisher Scientific, #4367659). Primers were designed across exon-exon junctions and the specificity of PCR products was checked by electrophoresis. n = 3 biologically independent replicates.

Cell number, viability, and cell death measurement

For cell number count, cells were washed with cold PBS, trypsinized, treated with Trypan Blue (ThermoFisher Scientific, #15250061), and counted on the hemocytometer. n = 3 biologically independent replicates. For viability measurement, cells were treated with CellTiter-Glo^® assay reagents (Promega, #G7570) (n = 3 biologically independent replicates) or Crystal Violet reagents (n = 3 biologically independent replicates), dissolved by 10% acetic acid and quantified by the absorbance at 570 nm. Cell death was measured by the CellTox Green Cytotoxicity assay reagents (Promega, #G8741) (n = 3 biologically independent replicates) at 485/520 nm at 0, 16, 19, 24, 40, 48, 73, and 96 h post reagent addition by the FLUOstar Optima (BMG lab tech).

Microarray, analysis, and GSEA analysis

Total RNAs were collected with RNeasy Mini Kit (Qiagen, #74104) and assessed with the Agilent BioAnalyzer. cDNAs were generated from 200 ng RNA using the Ambion MessageAmp Premier RNA Amplification (Life Technologies, Grand Island NY, USA) and were interrogated with Affymetrix U133A GeneChip. Gene expression data were deposited into NCBI GEO (GSE135358, GSE135346, and GSE147062). The microarray data were normalized by the RMA (Robust Multi-Array) algorithm. and zero transformed to the negative control (siNT), where we compared transcript levels for each gene in siMESH1 groups to the siNT group (n = 3 biologically independent replicates in each siRNA group) as previously performed [7, 9, 48]. Data were then filtered with Cluster 3.0 until ~1000 probesets were left and clustered by the gene. Heat maps were generated with TreeView with the indicated intensity. For GSEA analysis, siMESH1 vs. siNT microarray data were compared with the TAZ and YAP-induced genesets in the Supplementary table S1 in Zhang H, et al. [29]. (gene fold change ≤12-fold were cut off) using the Gene Set Enrichment Analysis (GSEA) performed at Broad Public Server with a default setting of 1000 permutations.

BrdU incorporation assay

H1975 cells transduced with indicated inducible shRNAs were seeded in six-well plates and treated with doxycycline for 48 h, and then were transferred to four-well chamber slides (Sigma, #C6932-1PAK) 1 day prior to labeling. For labeling, cells were treated with 10 μM BrdU (ThermoFisher Scientific, #B23151) for 2 h at 37 °C, washed with warm PBS for 2 min three times, and fixed in 3.7% formaldehyde in PBS for 15 min at RT, followed by the incubation of permeabilization buffer (0.1% Triton X-100 in PBS) for 20 min. Permeabilized cells were buffer changed to 1 N HCl for 10 min on ice, 2 N HCl for 10 min at RT, phosphate/citric acid buffer (pH 7.4) for 10 min at RT, and washed with permeabilization buffer for 2 min three times. Processed cells were blocked with antibody staining solution (0.1% Triton X-100 + 5% normal goat serum in PBS) for 1 h at room temperature on a rocker and blotted with 1:100 anti-BrdU primary antibody (Abcam, #ab115874) overnight at 4 °C, followed by 1:500 anti-mouse Alexa-Flour 594 antibody (Abcam, #ab150116) for 1 h at RT, washed three times before being mounted with SlowFade Gold Antifade Mountant with DAPI (Invitrogen, #S36938), covered with the coverslips and imaged under a fluorescent microscope. n = 2 biologically independent replicates.

PI (Propidium Iodide) stain and flow cytometry

For cell cycle analysis, 2 × 10⁵ H1975 cells were reverse transfected with the indicated siRNAs for 72 h, harvested using 0.05% trypsin with the media, fixed in 3 mL of ice-cold 70% ethanol, and gently vortexed until suspended. Fixed cells were centrifuged for 5 min at 1000 rpm at room temperature and washed twice with 3 mL of PBS at room temperature. For PI stain, cells were resuspended in 0.5–1 mL of PBS with 25 μg/mL PI (Sigma, #P4864) and 10 ug/mL RNAse A for 30 min at room temperature, light protected. At least 10⁴ processed cells were measured on a Canto II Flow cytometer at last. Data were analyzed using the FlowJo V10 software and the gating strategy was shown in Supplementary Fig. 4c. n = 3 biologically independent replicates.

dNTP measurement

H1975 and RCC4 cells were transfected with the indicated siRNAs for 3 days, washed with ice-cold PBS twice, lysed by ice-cold 65% methanol, scrapped off, and extra 100 μL of 65% methanol were added to the plate to recover all the material. Lysates were vigorously vortexed for 2 min in 4 °C, incubated at 95 °C for 3 min, chilled on ice for 1 min, and centrifuge in 4 °C, 14,000 RPM for 3 min. The supernatant was dried by speed vacuum and analyzed in Kim’s lab at Emory University for dNTP quantification using HIV reverse transcriptase-based assay [49]. n = 3 biologically independent replicates.

Animal study and xenograft

H1975 was transduced with empty vector (Tet-pLKO-puro, Addgene #21915, a gift from Dmitri Wiederschain) or shRNAs targeting MESH1 (shMESH1-1 and shMESH1-2) or AHR (shAHR-1 and shAHR-2). A single-cell colony for each shRNA was selected. About 1 × 10⁶ cells were injected subcutaneously in 0.1 ml of a 1:1 media to Matrigel (Corning, #354234) solution into the lower right flank of female immunodeficient mice (C.B-17 scid mice from Taconic lab) (empty vector: n = 7 biologically independent replicates, shMESH1-1: n = 9 biologically independent replicates, shMESH1-2: n = 8 biologically independent replicates, shMESH1-2 + TAZS89A OE: n = 9 biologically independent replicates, shAHR-1: n = 9 biologically independent replicates, shAHR-2: n = 9 biologically independent replicates). Once tumors were palpable (~1 week), all mice were switched to a doxycycline diet (Harlan, TD.110720, 2–3 mg doxycycline/day) for induction of shRNA. Tumor volumes were measured every other day using digital calipers until tumors reached 1.5–2 cm³, at which time mice were euthanized by carbon dioxide chamber, and tumors were harvested for weight measurement. Mice could also be euthanized if they became moribund or met other IACUC defined criteria suggesting pain or distress (e.g., weight loss >15%, ruffled fur, etc.) in the approved protocol by Duke IACUC (Registry Number A119-06-21.) During the course of xenograft injections and measurement, mice were handled randomly and blindly (only the ear numbers were given during the data collection process).

Tumor sphere formation assay

About 0.7 × 10⁵ indicated H1975 cells were seeded in each well of the six-well plate in normal media, and 24 h later were treated with or without 2 μg/mL Doxycyclin for 48 h. A total of 7000 cells were then transferred to the 24-well low-attachment plate (Corning, #CLS3473) in CCSC media in replicates (n = 3) and were cultured for 10 days before counting. Control or doxycycline-containing CCSC media were added every 4 days to maintain knockdown. Tumor spheres were counted under the microscope by diameter size: II: 100–200 μm; III: 200–300 μm; IV: 300–400 μm; V: >400 μm. Three technical replicates were averaged to represent each biological replicate. n = 3 biologically independent replicates.

Limited dilution assay

About 0.7 × 10⁵ indicated H1975 cells were seeded in a six-well plate in normal media and treated with or without 2 μg/mL Doxycycline for 48 h. Cells were then serial diluted to the 96-well round-bottom low-attachment plate (Corning, #7007) with 1000, 500, 100, 50 cells/well in CCSC media with technical replicates of 48 for each cell density. Spheres were cultured in CCSC media for 8 days before counting. Doxycycline-containing or deficient (no doxy control) CCSC media were added to each well every 4 days to maintain the knockdown level. After 8 days, the number of wells that successfully formed tumor sphere out of the 48 replicates for each cell density in each group was counted and data were plugged into the Extreme Limiting Dilution Analysis (ELDA) algorithm [50] for stem cell frequency, p value, and confidence interval calculations.

ChIP-qPCR

Five million H1975 cells were seeded in 15 cm dishes and transfected with the siRNAs (siNT and siMESH1s) for 72 h before cross-link and collection of the cell lysates. Myers Lab ChIP-seq Protocol v011014-Adherent cells was then followed (https://www.encodeproject.org/documents/6ecd8240-a351-479b-9de6-f09ca3702ac3/@@download/attachment/ChIP-seq_Protocol_v011014.pdf). Sonication condition was optimized to the High mode, 30 s on/30 s off at 4 °C for 45 min using the Bioruptor Twin (Diagenode) sonicator. Dynabeads Protein G (Invitrogen, #10003D) and anti-H3K27Ac (Cell Signaling Technology, #8173), anti-TAZ (Cell Signaling Technology, #70148), anti-AHR (Santa Cruz Biotechnology, #sc-133088 X) or rabbit IgG (negative control: Santa Cruz Technology, sc-66931), mouse IgG (Santa Cruz Technology, sc-2025) were used for pull-down in this study as instructed. Pulled down DNA was then mixed with primers targeting the TAZ promoter, or YAP promoter, or TAZ-proximal heterochromatin region together with the Power SYBRGreen Mix (ThermoFisher Scientific, #4367659) to undergo the qPCR reaction as described above. Primers were designed following the guidelines on the Michigan University Nutritional Sciences website (http://bridgeslab.sph.umich.edu/protocols/index.php/RT-PCR_primer_design_for_ChIP). n = 3 biologically independent replicates.

Co-immunoprecipitation

H1975 cells were transfected with the indicated vectors for 48 h. Cells were washed with PBS and resuspended in lysis buffer (50 mM Tris-HCl, 150 mM NaCl, 1% NP-40 and 5 mM EDTA, protease inhibitor cocktail, phosphatase inhibitor cocktail) at 4 °C with shaking for 30 min. Cell debris was pelleted by centrifugation at 16,000 × g for 15 min at 4 °C. Immunoprecipitation was performed using anti-FLAG (Anti-Flag M2 Affinity Gel, Sigma-Aldrich, #A2220) agarose beads at 4 °C overnight, washed three times and eluted using SDS loading buffer at 95 °C for 15 min, followed by the western blot using anti-HA (CST, #3724) and anti-FLAG (CST, #14793). n = 2 biologically independent replicates.

MESH1 clinical relevance analysis

The expression of MESH1/HDDC3 as the probeset 227008_at (Affymetrix) or RNA-Seq were analyzed using prognostic database KM plotter, OncoLnc [51], and PROGgene V2.

Statistical analysis and data collection

n numbers of biologically independent replicates were included in each figure legend and illustrated by the individual data points in each bar graph (mean + s.d.). The sample size was chosen based on our previous experience and literature reports for each experiment. P values were calculated by the indicated statistical analysis methods described in each figure legend and were justified as appropriate. Data collection was assigned blindly to different researchers.

Data availability

The data that support the findings of this study are available from the corresponding authors upon request. The microarray data have been deposited into NCBI GEO with accession numbers: GSE135358, GSE135346, and GSE147062.

References

Chi JT, Wang Z, Nuyten DS, Rodriguez EH, Schaner ME, Salim A, et al. Gene expression programs in response to hypoxia: cell type specificity and prognostic significance in human cancers. PLoS Med. 2006;3:e47.
Article PubMed PubMed Central Google Scholar
Keenan MM, Liu B, Tang X, Wu J, Cyr D, Stevens RD, et al. ACLY and ACC1 regulate hypoxia-induced apoptosis by modulating ETV4 via alpha-ketoglutarate. PLoS Genet. 2015;11:e1005599.
Article PubMed PubMed Central Google Scholar
Chen JL, Lucas JE, Schroeder T, Mori S, Wu J, Nevins J, et al. The genomic analysis of lactic acidosis and acidosis response in human cancers. PLoS Genet. 2008;4:e1000293.
Article PubMed PubMed Central Google Scholar
Chen JL, Merl D, Peterson CW, Wu J, Liu PY, Yin H, et al. Lactic acidosis triggers starvation response with paradoxical induction of TXNIP through MondoA. PLoS Genet. 2010;6:e1001093.
Article PubMed PubMed Central Google Scholar
Lamonte G, Tang X, Chen JL, Wu J, Ding CK, Keenan MM, et al. Acidosis induces reprogramming of cellular metabolism to mitigate oxidative stress. Cancer Metab. 2013;1:23.
Article PubMed PubMed Central Google Scholar
Gatza ML, Kung HN, Blackwell KL, Dewhirst MW, Marks JR, Chi JT. Analysis of tumor environmental response and oncogenic pathway activation identifies distinct basal and luminal features in HER2-related breast tumor subtypes. Breast Cancer Res. 2011;13:R62.
Article PubMed PubMed Central Google Scholar
Tang X, Ding CK, Wu J, Sjol J, Wardell S, Spasojevic I, et al. Cystine addiction of triple-negative breast cancer associated with EMT augmented death signaling. Oncogene 2017;36:4379.
Article CAS PubMed Google Scholar
Tang X, Keenan MM, Wu J, Lin CA, Dubois L, Thompson JW, et al. Comprehensive profiling of amino acid response uncovers unique methionine-deprived response dependent on intact creatine biosynthesis. PLoS Genet. 2015;11:e1005158.
Article PubMed PubMed Central Google Scholar
Tang X, Wu J, Ding CK, Lu M, Keenan MM, Lin CC, et al. Cystine deprivation triggers programmed necrosis in VHL-deficient renal cell carcinomas. Cancer Res. 2016;76:1892–903.
Article CAS PubMed PubMed Central Google Scholar
Potrykus K, Cashel M. (p)ppGpp: still magical? Annu Rev Microbiol. 2008;62:35–51.
Article CAS PubMed Google Scholar
Kriel A, Bittner AN, Kim SH, Liu K, Tehranchi AK, Zou WY, et al. Direct regulation of GTP homeostasis by (p)ppGpp: a critical component of viability and stress resistance. Mol Cell. 2012;48:231–41.
Article CAS PubMed PubMed Central Google Scholar
Wang B, Dai P, Ding D, Del Rosario A, Grant RA, Pentelute BL, et al. Affinity-based capture and identification of protein effectors of the growth regulator ppGpp. Nat Chem Biol. 2019;15:141–50.
Article PubMed Google Scholar
Sun D, Lee G, Lee JH, Kim HY, Rhee HW, Park SY, et al. A metazoan ortholog of SpoT hydrolyzes ppGpp and functions in starvation responses. Nat Struct Mol Biol. 2010;17:1188–94.
Article CAS PubMed Google Scholar
Ding C-KC, Rose J, Sun T, Wu J, Chen P-H, Lin C-C, et al. MESH1 is a cytosolic NADPH phosphatase that regulates ferroptosis. Nature. Metabolism 2020;2:270–7.
CAS Google Scholar
Khan S, Greco D, Michailidou K, Milne RL, Muranen TA, Heikkinen T, et al. MicroRNA related polymorphisms and breast cancer risk. PLoS One. 2014;9:e109973.
Article PubMed PubMed Central Google Scholar
Bild AH, Yao G, Chang JT, Wang Q, Potti A, Chasse D, et al. Oncogenic pathway signatures in human cancers as a guide to targeted therapies. Nature 2006;439:353–7.
Article CAS PubMed Google Scholar
Tripathi MK, Deane NG, Zhu J, An H, Mima S, Wang X, et al. Nuclear factor of activated T-cell activity is associated with metastatic capacity in colon cancer. Cancer Res. 2014;74:6947–57.
Article CAS PubMed PubMed Central Google Scholar
Lee Y, Liu J, Patel S, Cloughesy T, Lai A, Farooqi H, et al. Genomic landscape of meningiomas. Brain Pathol. 2010;20:751–62.
Article CAS PubMed Google Scholar
Leich E, Salaverria I, Bea S, Zettl A, Wright G, Moreno V, et al. Follicular lymphomas with and without translocation t(14;18) differ in gene expression profiles and genetic alterations. Blood. 2009;114:826–34.
Article CAS PubMed PubMed Central Google Scholar
Durfee T, Hansen AM, Zhi H, Blattner FR, Jin DJ. Transcription profiling of the stringent response in Escherichia coli. J Bacteriol. 2008;190:1084–96.
Article CAS PubMed Google Scholar
Reichard P. Interactions between deoxyribonucleotide and DNA synthesis. Annu Rev Biochem. 1988;57:349–74.
Article CAS PubMed Google Scholar
Nordlund P, Reichard P. Ribonucleotide reductases. Annu Rev Biochem. 2006;75:681–706.
Article CAS PubMed Google Scholar
Cordenonsi M, Zanconato F, Azzolin L, Forcato M, Rosato A, Frasson C, et al. The Hippo transducer TAZ confers cancer stem cell-related traits on breast cancer cells. Cell. 2011;147:759–72.
Article CAS PubMed Google Scholar
Zhao B, Lei QY, Guan KL. The Hippo-YAP pathway: new connections between regulation of organ size and cancer. Curr Opin Cell Biol. 2008;20:638–46.
Article CAS PubMed PubMed Central Google Scholar
Zanconato F, Cordenonsi M, Piccolo S. YAP/TAZ at the roots of cancer. Cancer Cell. 2016;29:783–803.
Article CAS PubMed PubMed Central Google Scholar
Yang W-H, Lin C-C, Wu J, Chao P-Y, Chen K, Chen P-H, et al. The Hippo pathway effector YAP promotes ferroptosis via the E3 ligase SKP2. Mol Cancer Res. 2021;19:1005–14.
Article CAS PubMed PubMed Central Google Scholar
Yang W-H, Ding C-KC, Sun T, Rupprecht G, Lin C-C, Hsu D, et al. pathway effector TAZ regulates ferroptosis in renal cell carcinoma. Cell Rep. 2019;28:1–8.e4.
Article Google Scholar
Yang WH, Huang Z, Wu J, Ding C-KC, Murphy SK, Chi J-T. A TAZ-ANGPTL4-NOX2 axis regulates ferroptotic cell death and chemoresistance in epithelial ovarian cancer. Mol Cancer Res. 2019;18:79–90.
Article PubMed PubMed Central Google Scholar
Zhang H, Liu CY, Zha ZY, Zhao B, Yao J, Zhao S, et al. TEAD transcription factors mediate the function of TAZ in cell growth and epithelial-mesenchymal transition. J Biol Chem. 2009;284:13355–62.
Article CAS PubMed PubMed Central Google Scholar
Lin CC, Ding CC, Sun T, Wu J, Chen KY, Zhou P, et al. The regulation of ferroptosis by MESH1 through the activation of the integrative stress response. Cell Death Dis. 2021;12:727.
Article CAS PubMed PubMed Central Google Scholar
Lei Q-Y, Zhang H, Zhao B, Zha Z-Y, Bai F, Pei X-H, et al. TAZ promotes cell proliferation and epithelial-mesenchymal transition and is inhibited by the Hippo pathway. Mol Cell Biol. 2008;28:2426–36.
Article CAS PubMed PubMed Central Google Scholar
Zanconato F, Forcato M, Battilana G, Azzolin L, Quaranta E, Bodega B, et al. Genome-wide association between YAP/TAZ/TEAD and AP-1 at enhancers drives oncogenic growth. Nat Cell Biol. 2015;17:1218–27.
Article CAS PubMed PubMed Central Google Scholar
Fishilevich S, Nudel R, Rappaport N, Hadar R, Plaschkes I, Iny Stein T, et al. GeneHancer: genome-wide integration of enhancers and target genes in GeneCards. Database. 2017;2017:bax028.
Article PubMed Central Google Scholar
Konermann S, Brigham MD, Trevino AE, Joung J, Abudayyeh OO, Barcena C, et al. Genome-scale transcriptional activation by an engineered CRISPR-Cas9 complex. Nature 2015;517:583–8.
Article CAS PubMed Google Scholar
Glozak MA, Seto E. Histone deacetylases and cancer. Oncogene 2007;26:5420–32.
Article CAS PubMed Google Scholar
Haberland M, Montgomery RL, Olson EN. The many roles of histone deacetylases in development and physiology: implications for disease and therapy. Nat Rev Genet. 2009;10:32–42.
Article CAS PubMed PubMed Central Google Scholar
Stark C, Breitkreutz BJ, Reguly T, Boucher L, Breitkreutz A, Tyers M. BioGRID: a general repository for interaction datasets. Nucleic Acids Res 2006;34:D535–9.
Article CAS PubMed Google Scholar
CLC Bio QIAGEN. White paper on the transcription factor ChIP-seq. 2015. https://resources.qiagenbioinformatics.com/white-papers/Transcription_factor_ChIP-seq.pdf?_ga=2.219229657.1909906395.1620224188-1671251113.1620224188.
Oshima M, Mimura J, Sekine H, Okawa H, Fujii-Kuriyama Y. SUMO modification regulates the transcriptional repressor function of aryl hydrocarbon receptor repressor. J Biol Chem. 2009;284:11017–26.
Article CAS PubMed PubMed Central Google Scholar
Hong W, Guan KL. The YAP and TAZ transcription co-activators: key downstream effectors of the mammalian Hippo pathway. Semin Cell Dev Biol. 2012;23:785–93.
Article CAS PubMed PubMed Central Google Scholar
Sun T, Chi J-T. Regulation of ferroptosis in cancer cells by YAP/TAZ and Hippo pathways: the therapeutic implications. Genes Dis. 2020;8:241–9.
Article PubMed PubMed Central Google Scholar
Dupont S, Morsut L, Aragona M, Enzo E, Giulitti S, Cordenonsi M, et al. Role of YAP/TAZ in mechanotransduction. Nature. 2011;474:179–83.
Article CAS PubMed Google Scholar
Zhao B, Wei X, Li W, Udan RS, Yang Q, Kim J, et al. Inactivation of YAP oncoprotein by the Hippo pathway is involved in cell contact inhibition and tissue growth control. Genes Dev. 2007;21:2747–61.
Article CAS PubMed PubMed Central Google Scholar
Liu CY, Yu T, Huang Y, Cui L, Hong W. ETS (E26 transformation-specific) up-regulation of the transcriptional co-activator TAZ promotes cell migration and metastasis in prostate cancer. J Biol Chem. 2017;292:9420–30.
Article CAS PubMed PubMed Central Google Scholar
Liu CY, Chan SW, Guo F, Toloczko A, Cui L, Hong W. MRTF/SRF dependent transcriptional regulation of TAZ in breast cancer cells. Oncotarget. 2016;7:13706–16.
Article PubMed PubMed Central Google Scholar
Hilman D, Gat U. The evolutionary history of YAP and the hippo/YAP pathway. Mol Biol Evol. 2011;28:2403–17.
Article CAS PubMed Google Scholar
Yang Z, Nakagawa K, Sarkar A, Maruyama J, Iwasa H, Bao Y, et al. Screening with a novel cell-based assay for TAZ activators identifies a compound that enhances myogenesis in C2C12 cells and facilitates muscle repair in a muscle injury model. Mol Cell Biol. 2014;34:1607–21.
Article PubMed PubMed Central Google Scholar
Lin CC, Mabe NW, Lin YT, Yang WH, Tang X, Hong L, et al. RIPK3 upregulation confers robust proliferation and collateral cystine-dependence on breast cancer recurrence. Cell Death Differ. 2020;27:2234–47.
Article CAS PubMed PubMed Central Google Scholar
Diamond TL, Roshal M, Jamburuthugoda VK, Reynolds HM, Merriam AR, Lee KY, et al. Macrophage tropism of HIV-1 depends on efficient cellular dNTP utilization by reverse transcriptase. J Biol Chem. 2004;279:51545–53.
Article CAS PubMed Google Scholar
Hu Y, Smyth GK. ELDA: extreme limiting dilution analysis for comparing depleted and enriched populations in stem cell and other assays. J Immunol Methods. 2009;347:70–8.
Article CAS PubMed Google Scholar
Anaya. OncoLnc: linking TCGA survival data to mRNAs, miRNAs, and lncRNAs. PeerJ Comput Sci. 2016;2:e67.
Article Google Scholar

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Acknowledgements

We thank members of Chi lab for technical assistance and critical feedback.

Funding

This work was supported by DOD (W81XWH-17-1-0143, W81XWH-15-1-0486, and DOD KC180120) and NIH (R01GM124062 to J-TC and R01GM117106 to RG). The dNTP measurement was funded by R01 AI136581 and AI162633 to BK.

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These authors contributed equally: Tianai Sun, Chien-Kuang Cornelia Ding.

Authors and Affiliations

Department of Molecular Genetics and Microbiology, Duke University, Durham, NC, 27710, USA
Tianai Sun, Chien-Kuang Cornelia Ding, Yang Zhang, Chao-Chieh Lin, Jianli Wu, Yasaman Setayeshpour, Raluca Gordân & Jen-Tsan Chi
Center for Genomic and Computational Biology, Duke University, Durham, NC, 27708, USA
Tianai Sun, Chien-Kuang Cornelia Ding, Yuning Zhang, Yang Zhang, Chao-Chieh Lin, Jianli Wu, Yasaman Setayeshpour, Raluca Gordân & Jen-Tsan Chi
Program in Computational Biology and Bioinformatics, Duke University, Durham, NC, 27708, USA
Yuning Zhang & Jen-Tsan Chi
Center for Drug Discovery, Department of Pediatrics, School of Medicine, Emory University, Atlanta, GA, 30322, USA
Si’Ana Coggins, Caitlin Shepard & Baek Kim
Department of Pathology, Duke University, Durham, NC, 27708, USA
Everardo Macias
Department of Biochemistry, Duke University School of Medicine, Durham, NC, 27710, USA
Pei Zhou
Department of Biostatistics and Bioinformatics, Duke University Medical Center, Durham, NC, 27710, USA
Raluca Gordân
Department of Computer Science, Duke University, Durham, NC, 27708, USA
Raluca Gordân

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Tianai Sun
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Contributions

The experimental concept was originally conceived by J-TC and developed by TS and C-KCD. Mouse xenografts were done by TS and C-KCD. Cell culture and the in vitro assays were done by TS with assistance from C-KCD, YZ, C-CL, JW, and YS. dNTP measurements were done by SAC, CS, and BK. Incucyte analysis was done by TS with assistance from EM. Transcription factor motif binding map was generated by TS with the assistance from YZ and RG. TS and J-TC wrote the manuscript with assistance from other co-authors.

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Correspondence to Jen-Tsan Chi.

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Supplemental Material-original western blots

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Sun, T., Ding, CK.C., Zhang, Y. et al. MESH1 knockdown triggers proliferation arrest through TAZ repression. Cell Death Dis 13, 221 (2022). https://doi.org/10.1038/s41419-022-04663-6

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Received: 24 August 2021
Revised: 04 February 2022
Accepted: 14 February 2022
Published: 10 March 2022
DOI: https://doi.org/10.1038/s41419-022-04663-6