mcPGK1-dependent mitochondrial import of PGK1 promotes metabolic reprogramming and self-renewal of liver TICs

Chen, Zhenzhen; He, Qiankun; Lu, Tiankun; Wu, Jiayi; Shi, Gaoli; He, Luyun; Zong, Hong; Liu, Benyu; Zhu, Pingping

doi:10.1038/s41467-023-36651-5

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Published: 27 February 2023

mcPGK1-dependent mitochondrial import of PGK1 promotes metabolic reprogramming and self-renewal of liver TICs

Nature Communications volume 14, Article number: 1121 (2023) Cite this article

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Abstract

Liver tumour-initiating cells (TICs) contribute to tumour initiation, metastasis, progression and drug resistance. Metabolic reprogramming is a cancer hallmark and plays vital roles in liver tumorigenesis. However, the role of metabolic reprogramming in TICs remains poorly explored. Here, we identify a mitochondria-encoded circular RNA, termed mcPGK1 (mitochondrial circRNA for translocating phosphoglycerate kinase 1), which is highly expressed in liver TICs. mcPGK1 knockdown impairs liver TIC self-renewal, whereas its overexpression drives liver TIC self-renewal. Mechanistically, mcPGK1 regulates metabolic reprogramming by inhibiting mitochondrial oxidative phosphorylation (OXPHOS) and promoting glycolysis. This alters the intracellular levels of α-ketoglutarate and lactate, which are modulators in Wnt/β-catenin activation and liver TIC self-renewal. In addition, mcPGK1 promotes PGK1 mitochondrial import via TOM40 interactions, reprogramming metabolism from oxidative phosphorylation to glycolysis through PGK1-PDK1-PDH axis. Our work suggests that mitochondria-encoded circRNAs represent an additional regulatory layer controlling mitochondrial function, metabolic reprogramming and liver TIC self-renewal.

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Introduction

Liver cancer is a common tumor type and many liver cancer patients have a very poor prognosis, which is largely due to tumor heterogeneity¹. Accumulating researches have proved that tumor heterogeneity originates from the hierarchic organization of tumor cells that are derived from a small population of cells, termed as tumor initiating cells (TICs) or cancer stem cells (CSCs)¹. Several markers of liver TICs (or CSCs) have been identified, such as CD133, CD13 and ZIC2^2,3,4. Unlike differentiated cancer cells, TICs are resistant to traditional radiotherapy and chemotherapy, and increasing studies demonstrate that TICs are also insensitive to CAR-T and immune checkpoint therapies^5,6. Liver TICs is regulated by Wnt/β-catenin^7,8, Notch⁹, Hedgehog¹⁰ and Hippo/Yap signaling pathways¹¹, and these pathways are further accurately modulated. However, the molecular mechanisms of liver TIC function remain elusive.

Circular RNAs (circRNAs) are newly identified regulatory RNA molecules that have emerged as critical modulators in multiple biological processes¹². Several circRNAs are identified as microRNA sponges, such as ciRS-7/CDR1as^13,14. Fusion circRNAs and rtcircRNA are involved in tumorigenesis and drug-resistance^15,16. We have identified circPan3 and circKcnt2 as regulators in intestinal stem cell (ISC) and colitis, respectively^17,18. Moreover, we also revealed some circRNAs involved in the self-renewal regulation of tumor cells and TICs, including cia-MAF¹⁹, cis-HOX²⁰ and circREEP3²¹. Recently, mitochondria-encoded circRNAs have been identified, which are involved in communication between mitochondria and the nucleus²². Nonalcoholic steatohepatitis (NASH)-related mitochondrial circRNA SCAR (abbreviated for Steatohepatitis-associated circRNA ATP5B Regulator) interacts with ATP5B and inhibits mitochondrial reactive oxygen species (mROS) production and fibroblast activation²³. However, the functions and regulatory mechanisms of mitochondria-encoded circRNAs in tumorigenesis and TICs are hitherto unclear.

Mitochondria are the key energy factories in almost all eukaryote cells. Mitochondria contain their own DNA, which encodes mitochondria-specific proteins and noncoding RNAs, such as 16 S ribosomal RNA, some transfer RNAs and circRNAs²⁴. Mitochondria contain 1000–3000 proteins, most of which are encoded by nuclear DNA and transported from the cytoplasm by mitochondrial translocases, such as the TOM40 complex^25,26. Many metabolic processes, including oxidative phosphorylation (OXPHOS), fatty acid β-oxidation and the urea cycle, occur in mitochondria^27,28. These metabolic processes are regulated by various intracellular and extracellular factors. Recently, we have revealed that a mitochondria-located methyltransferase, Mettl4, inhibits mitochondrial transcription, OXPHOS, glycolysis, and mROS production²⁹. Morphological and functional alterations of mitochondria are also driven by a variety of external factors, including hypoxia, starvation, infection, and tumorigenesis^30,31. A hallmark of tumorigenesis is metabolic reprogramming, in which the main metabolic pathway switches from OXPHOS to glycolysis, a process also known as the Warburg effect³². One possible necessary of metabolic reprogramming is that some intermediate products of glycolysis provide a material basis for the rapid propagation of tumor cells. Indeed, the activities of glycolysis and OXPHOS are adjusted in cells within various stages of cell cycle. Cells in G1 stage prefer OXPHOS, whereas cells in S stage prefer glycolysis³³. In addition to energy production, glycolysis and OXPHOS produce various metabolites that regulate multiple intracellular and extracellular biological processes. For example, the production of lactic acid during glycolysis inhibits the activity of T cells, enabling the immune escape of tumor cells³⁴. In the present study, we have characterized a mitochondrial circRNA, termed mcPGK1 (mitochondrial circRNA for translocating phosphor- glycerate kinase 1), which is highly expressed in liver TICs and liver tumors. We found that mcPGK1 promotes the mitochondrial localization of PGK1, contributes to the metabolic reprogramming from OXPHOS to glycolysis.

Results

McPGK1 is highly expressed in liver TICs

Mitochondrial DNA-encoded circular RNAs (mecircRNAs) emerge as a new type of circRNAs²², and have been identified as critical modulators in NASH²³, but their functions in tumorigenesis and TIC self-renewal are unknown. Here, we sorted CD133⁺ cells from primary liver cancer and proved these cells as liver TICs (Supplementary Fig. 1A–C), and isolated mitochondria from liver TICs and non-TICs for circRNA sequencing. There were 54 mecircRNAs identified in liver cancer cells. Among them, 9 mecircRNAs were differentially expressed (FC > 2, P-value < 0.05) in liver TICs and non-TICs, and named mecirc1-9 according to their corresponding locus of mitochondrial DNA (Fig. 1A). Then we designed circRNA-specific primers (Supplementary Fig. 1D) and detected their expression levels in six pairs of liver tumor and peri-tumor samples, and eight mecircRNAs were differently expressed in liver tumors (Supplementary Fig. 1E). Four pairs of TICs and non-TICs were used to further analyze mecircRNA expression, and finally six mecircRNAs (mecirc4, mecirc5, mecirc6, mecirc7, mecirc8, mecirc9) were screened out (Supplementary Fig. 1F, G). RNase R digestion, PCR and DNA-sequencing also confirmed that these six mecircRNAs are circular RNA (Supplementary Fig. 1H, I).

**Fig. 1: High expression of *mcPGK1* in liver tumor and liver TICs.**

To identify functional mecircRNA, we generated mecircRNA overexpressing cells (Supplementary Fig. 2A, B), followed by TIC detection. mecirc4, mecirc5 and mecirc8 drove expression of TIC marker CD133, whereas mecirc5 and mecirc8 promoted c-Myc expression (Supplementary Fig. 2C). Moreover, sphere formation assay showed that mecirc5, mecirc6 and mecirc8 were involved in liver TIC self-renewal (Supplementary Fig. 2D), and we focused on mecirc8 (hereafter termed as mcPGK1) for further analysis. mcPGK1 was generated from CYTB locus of mitochondrial DNA (Supplementary Fig. 2E). Then mcPGK1 specific probe was screened out by RNase H digestion assay and real-time PCR detection (Supplementary Fig. 2F), and confirmed via fluorescence in situ hybridization (Supplementary Fig. 2G). About 400–800 copies of mcPGK1 were detected in each liver TIC or sphere cell (Supplementary Fig. 3A). Then the subcellular location of mcPGK1 was measured. mcPGK1 was enriched in cytosol factions (including mitochondria) but not enriched in nuclear fractions (Supplementary Fig. 3B). Then mitochondria were isolated from cytosol fractions, and mcPGK1 was predominantly localized in mitochondria and also detectable in cytoplasm (Supplementary Fig. 3C–E). Moreover, total and mitochondrial mcPGK1 were increased in liver tumorigenesis (Supplementary Fig. 3F). We also examined the exact location of mcPGK1 in mitochondrial fractions isolated with APEX labeling, and found mcPGK1 was enriched in outer mitochondrial membrane and matrix, and also detectable in intermembrane space (Supplementary Fig. 3G, H). Fraction separation of mitochondria confirmed these results (Supplementary Fig. 3I). These data demonstrated that mcPGK1 was a mitochondrial DNA-encoded circular RNA and preferentially located in mitochondria.

Tox further evaluate the expression signature of mcPGK1 in liver tumors, we performed mcPGK1 in situ hybridization and the results showed that mcPGK1 was highly expressed in liver tumors (Supplementary Fig. 4A). The expression of mcPGK1 was correlated with clinical stages, tumor volumes, relapse and survival (Fig. 1B and Supplementary Fig. 4B, C). mcPGK1 was co-expressed with CD133, a marker of TICs (Supplementary Fig. 4D). Samples with low mcPGK1 expression harbored fewer TICs, whereas samples with high mcPGK1 expression harbored more TICs (Fig. 1C). We also validated the upregulation of mcPGK1 in liver tumors through RNAscope (Fig. 1D). Moreover, mcPGK1 RNAscope signals were positively related to CD133 ratios, confirming the microarray data (Fig. 1D and Supplementary Fig. 4E, F). The high expression of mcPGK1 in spheres and CD133⁺ TICs was confirmed by real-time PCR (Fig. 1E), Northern blotting (Fig. 1F), fluorescence in situ hybridization (Fig. 1G and Supplementary Fig. 4H), and RNAscope (Fig. 1H). Cytoplasmic and mitochondrial fractions were also separated from non-TICs, TICs, non-sphere and sphere cells, and mcPGK1 was proved to be enriched in mitochondrial fractions, especially in mitochondria of sphere cells (Supplementary Fig. 4G). Of note, the mitochondrial levels were comparable between liver TICs and non-TICs (Supplementary Fig. 4I). Taken together, mitochondria-encoded mcPGK1 is upregulated in liver TICs.

McPGK1 drives the self-renewal of liver TIC

We then evaluated the function of mcPGK1 in liver TICs. First, we detected mcPGK1 expression levels across several HCC cell lines and primary samples, and found that it was differentially expressed among these cell lines and tissue samples (Supplementary Fig. 5A, B). We then constructed mcPGK1-knockdown cells using mcPGK1 high-expressing cells and shmcPGK1 was screened out to specifically target mcPGK1 but not linear RNA (Fig. 2A and Supplementary Fig. 5C, D). Moreover, mcPGK1 knockdown decreased both cytoplasmic and mitochondrial mcPGK1 levels, although knockdown efficiency of mitochondrial mcPGK1 was lower than cytoplasmic mcPGK1 (Supplementary Fig. 5E, F). McPGK1 silenced cells contained fewer liver TICs, and expressed lower levels of TIC markers and TIC-associated genes (Fig. 2B, C). The mcPGK1 silenced cells also displayed impaired sphere formation and proliferation capacities, but cell apoptosis was not influenced by mcPGK1 knockdown (Fig. 2D–F, and Supplementary Fig. 5G, H). Moreover, decreased tumor initiation and propagation capacity was detected in mcPGK1 silenced cells (Fig. 2G–I). We then obtained shmcPGK1 CD133⁺ liver TICs and shmcPGK1 sphere cells for self-renewal detection, and revealed that mcPGK1 promotes self-renewal in liver TICs (Fig. 2J and Supplementary Fig. 5I). To further target mitochondrial mcPGK1 efficiently, we also constructed mitochondria-targeting nanoparticles²⁵, and found these nanoparticles can efficiently target mitochondrial mcPGK1 (Supplementary Fig. 5J). shmcPGK1 cells established by mitochondria-targeting nanoparticles also showed impaired sphere formation capacity (Fig. 2K).

**Fig. 2: *McPGK1* is required for liver TIC self-renewal.**

We also constructed mcPGK1 overexpressing cells, which also showed mitochondrial location of mcPGK1 (Supplementary Fig. 6A–C). These cells harbored increased TIC ratios and TIC marker expression (Supplementary Fig. 6D, E). Furthermore, mcPGK1 overexpression enhanced TIC self-renewal, tumor initiation but not apoptosis (Supplementary Fig. 6F–I). mcPGK1 was then overexpressed using mitochondria-targeting nanoparticles, and mcPGK1 overexpression in mitochondria also promoted liver TIC self-renewal (Supplementary Fig. 6J, K). Moreover, mcPGK1 overexpression also drove tumor propagation in vivo (Supplementary Fig. 6L). Overall, these findings indicate that mcPGK1 is required for liver TIC self-renewal.

McPGK1 reprograms metabolism from OXPHOS to glycolysis

As the central function of mitochondria is energy metabolism, we evaluated the effects of mcPGK1 on OXPHOS and glycolysis. OXPHOS activity was enhanced and glycolytic activity was attenuated in mcPGK1-silenced cells, whereas the opposite occurred in mcPGK1-overexpressing cells, indicating critical roles of mcPGK1 in metabolic reprogramming shifting from OXPHOS to glycolysis (Fig. 3A, B). Supporting these findings, the OXPHOS metabolite levels were increased and glycolytic metabolite levels were decreased in mcPGK1-silenced cells, whereas mcPGK1-overexpressing cells contained increased levels of glycolytic metabolites (Fig. 3C). Interestingly, divergent levels of OXPHOS and glycolysis metabolites were detected in primary cells with high or low mcPGK1 expression (Fig. 3D). These results demonstrate the essential role of mcPGK1 in metabolic reprogramming of liver TICs.

**Fig. 3: *McPGK1* drives the metabolic reprogramming from OXPHOS to glycolysis.**

We then determined the time-course levels of lactic acid and α-KG, two of the main metabolites of glycolysis and OXPHOS, respectively. Lactic acid accumulated rapidly in mcPGK1-overexpressing cells, but not in mcPGK1-knockdown cells (Fig. 3E). In contrast, α-KG was accumulated rapidly in mcPGK1-knockdown cells, but not in mcPGK1-overexpressing cells (Fig. 3F). Similarly, the medium of mcPGK1-overexpressing cells tended to become orange/yellow, whereas the medium of mcPGK1-silenced cells tended to stay red, confirming the role of mcPGK1 in the acidification of culture medium (Fig. 3G). These data demonstrated that mcPGK1 was involved in metabolic reprogramming.

Metabolic reprogramming drives liver TIC function via Wnt pathway

The functions of metabolic reprogramming in liver TICs are unknown. Among the metabolites we evaluated, lactic acid and α-KG functioned as stemness modulators in liver TICs (Fig. 4A). Lactic acid drove liver TIC self-renewal, whereas α-KG had an opposite effect (Fig. 4B, C). Lactic acid treatment increased the expression of TIC-associated genes, whereas α-KG elicited opposite effects (Fig. 4D). Then the roles of lactic acid and α-KG in liver tumor propagation and liver TIC self-renewal were examined in vivo. FX-11, an inhibitor of lactic acid production, inhibited liver tumor propagation (Fig. 4E and Supplementary Fig. 7A), decreased the ratios of CD133⁺ liver TICs (Fig. 4F), and impaired the tumor initiation capacity (Fig. 4G), indicating that lactic acid was a driver of liver TIC self-renewal. In contrast with lactic acid, α-KG showed inhibitory effects on liver tumor propagation and liver TIC maintenance (Fig. 4E–G). The modulation of liver tumor propagation by lactic acid and α-KG was confirmed by in vivo luciferase assay (Fig. 4H). These results confirmed that metabolic reprogramming was involved in liver TIC maintenance.

**Fig. 4: Lactate and α-KG are involved in liver TIC self-renewal.**

We evaluated several signaling pathways and found that lactic acid and α-KG both targeted Wnt/β-catenin pathway, a central signaling pathway for liver TIC function (Fig. 5A). The enhanced sphere-formation capacity by mcPGK1 was blocked upon Wnt/β-catenin inhibition with Wiki4 or LF3, further confirming that mcPGK1 exerted its role via Wnt/β-catenin pathway (Fig. 5B and Supplementary Fig. 7B). Lactic acid promoted Wnt/β-catenin activation and α-KG inhibited Wnt/β-catenin activation (Fig. 5C–F). Interestingly, β-catenin was increased at protein level but not mRNA level upon lactic acid treatment, and decreased at mRNA level upon DM-αKG treatment (Fig. 5C, F). As expected, lactic acid promoted β-catenin protein stability (Fig. 5G), and α-KG inhibited the activation of β-catenin promoter and β-catenin transcription (Fig. 5H, I). We then generated β-catenin silenced cells, and revealed that mcPGK1 had an impaired function in liver TIC self-renewal and in vivo propagation of liver tumor cells, confirming that mcPGK1 exerted its role mainly via a β-catenin-dependent manner (Supplementary Fig. 7C, D).

**Fig. 5: Lactate and α-KG are involved in Wnt/β-catenin activation.**

We then explored the molecular mechanism of lactic acid regulation of β-catenin protein stability. We previously identified lnc-β-catm as a modulator as β-catenin stability in liver cancer and TICs, via promoting the methylation of β-catenin³⁵, and here we investigated whether lactic acid promoted the expression of lnc-β-catm. We revealed that lactic acid promoted lnc-β-catm expression (Supplementary Fig. 7E), and subsequent β-catenin methylation (Supplementary Fig. 7F). Moreover, lactic acid displayed a limited role on β-catenin stability and sphere formation in lnc-β-catm knockout cells, indicating the critical role of lnc-β-catm in lactic acid-driven β-catenin stability (Supplementary Fig. 7G, H). We then explored the molecular mechanism of lactic acid in lnc-β-catm expression. Considering the direct effect of lactic acid on histone lactylation³⁶, we firstly detected the lactylation of lnc-β-catm promoter, and found that lactic acid promoted the histone lactylation of lnc-β-catm promoter at −700~−500 fragment (Supplementary Fig. 7I). We also deleted this region through CRISPR/Cas9 approach, and lactic acid didn’t promote lnc-β-catm expression upon lnc-β-catm promoter deletion (Supplementary Fig. 7J). These results proved that lactic acid promoted β-catenin stability largely through lnc-β-catm expression, which depends on histone lactylation of lnc-β-catm promoter.

Previous works have revealed that α-KG is a cofactor of H3K4me3 demethylase JARID1B^37,38, thus we investigated whether α-KG regulates the transcription of β-catenin through JARID1B-mediated H3K4me3 modification. We found α-KG inhibited H3K4me3 levels (Supplementary Fig. 8A). Moreover, α-KG inhibited the chromatin accessibility at CTNNB1 (β-catenin mRNA) promoter (Supplementary Fig. 8B). We also generated JARID1B silenced cells, and revealed that α-KG showed impaired roles in the H3K4me3 and accessibility of CTNNB1 promoter, as well as nascent CTNNB1 mRNA expression, upon JARID1B knockdown, indicating that α-KG inhibited β-catenin transcription through H3K4me3 demethylase JARID1B (Supplementary Fig. 8C–E). We also evaluated the function of α-KG with 2-HG, a competitive inhibitor of α-KG-dependent dioxygenases³⁸, and found that 2-HG largely attenuated the functions of α-KG in H3K4me3 enrichment, accessibility of CTNNB1 promoter and nascent CTNNB1 mRNA, further confirming that α-KG functions as a modulator of H3K4me3 demethylase (Supplementary Fig. 8F–H). These findings indicate that both lactic acid and α-KG function in liver TICs through Wnt/β-catenin pathway.

McPGK1 interacts with PGK1

To analyze the molecular mechanisms of mcPGK1, we performed an RNA pulldown assay, which identified PGK1, TOM40 and TOM70 as the partners of mcPGK1 in liver TICs (Fig. 6A). Immunoblot assay confirmed that mcPGK1 interacted with PGK1, TOM40 and TOM70 (Fig. 6B). We focused on PGK1, which is a critical modulator in glycolysis and OXPHOS³⁹. RNA immunoprecipitation proved PGK1-mcPGK1 interaction (Fig. 6C). We further analyzed the interaction of mcPGK1 and PGK1. Considering the critical role of stem-loop structures in RNA–protein interactions^40,41, we analyzed the structure of mcPGK1 and identified seven loops, and found that the second loop (HR#2) was required for the interaction between mcPGK1 and PGK1 (Fig. 6D, E, and Supplementary Fig. 8I). These results confirmed that mcPGK1 interacts with PGK1 in liver TICs.

**Fig. 6: *McPGK1* functions as PGK1 partner.**

We then examined whether the interaction with PGK1 was necessary for mcPGK1’s function. We generated cells that were overexpressing mutant mcPGK1, which lost the ability to interact with PGK1. Compared with wild-type mcPGK1, mutant mcPGK1 did not promote Wnt/β-catenin activation and liver TIC maintenance, further confirming the essential role of PGK1-mcPGK1 interaction (Fig. 6F, G). Moreover, mutant mcPGK1 showed an impaired role in tumor initiation (Fig. 6H). Altogether, mcPGK1 interacts with PGK1 and functions through mcPGK1-PGK1 interaction.

McPGK1 promotes the interaction of PGK1 and TOM40 complex

We then evaluated the combination between PGK1 and TOM40/TOM70, which are core components of TOM40 mitochondria importing complex⁴². We found that PGK1 interacted with TOM40 and TOM70, and their interactions were impaired in mcPGK1 silenced cells (Fig. 7A). On the contrary, enhanced interactions between PGK1 and TOM40/TOM70 were detected in mcPGK1 overexpressing cells (Fig. 7B). Enhanced interactions between PGK1 and TOM40/TOM70 were confirmed by co-immunoprecipitation assay supplemented with gradient mcPGK1 (Fig. 7C, D). Split-APEX2 assay confirmed the assembly of PGK1-TOM40/TOM70-mcPGK1 complex at outer mitochondrial membrane (Fig. 7E). Moreover, attenuated assembly of PGK1-TOM40/TOM70 complex was detected upon mcPGK1 knockdown (Fig. 7F). These results demonstrated that mcPGK1 promoted the interaction between PGK1 and TOM40/TOM70. Using mutant mcPGK1 transcripts, we found that the seventh loop (HR#7) was required for the interaction between mcPGK1 and TOM40/TOM70 (Fig. 7G). HR#2 mutant and HR#7 mutant mcPGK1 transcripts were overexpressed, which lost the ability to interact with PGK1 and TOM40/TOM70, respectively. Both mutant mcPGK1 transcripts (mut#2 and mut#7) weren’t involved in the regulation of PGK1-TOM40/TOM70 interaction, indicating that mcPGK1 served as a scaffold of PGK1-mcPGK1-TOM40/TOM70 complex (Fig. 7H). Moreover, #2 mutant and #7 mutant mcPGK1 weren’t involved in liver TIC self-renewal and metabolic reprogramming (Fig. 7I, J). HR#2 and HR#7 mutant mcGPK1 transcripts had impaired roles in PGK1-TOM40 interaction, TIC self-renewal and metabolic reprogramming, whereas WT mcGPK1 displayed these roles, thus we concluded that HR#2 and HR#7 were required for PGK1-TOM40/TOM70 interaction and mcPGK1-driven TIC self-renewal. Altogether, mcPGK1 promotes the binding of PGK1 to TOM40 mitochondrial importing complex.

**Fig. 7: *McPGK1* promotes the binding of PGK1 and TOM40 complex.**

McPGK1 drives the mitochondrial entry of PGK1

PGK1 is expressed in the cytoplasm, but is often translocated to the mitochondria during tumorigenesis, where it phosphorylates PDK1 at T338. In turn, PDK1 phosphorylates and inhibits the PDH complex, and thus inhibits OXPHOS and promotes glycolysis⁴³. Here, we demonstrated that mcPGK1 promoted the binding of PGK1 to TOM40 mitochondria importing complex. Therefore we examined the involvement of mcPGK1 in the translocation of PGK1 to mitochondria and found that this translocation was suppressed in mcPGK1 silenced cells, and increased in mcPGK1 overexpressing cells (Fig. 8A). However, PGK1 expression wasn’t influenced by mcPGK1 (Supplementary Fig. 9A). Immuno-electron microscopy also revealed that mcPGK1 was involved in mitochondrial translocation of PGK1 (Fig. 8B). Mitochondrial isolation and immunoblot confirmed that mcPGK1 was essential for PGK1 mitochondrial translocation (Fig. 8C). The positive role of mcPGK1 in PGK1 mitochondrial entry was further confirmed by mitochondrial fraction separation assay (Fig. 8D, E). We then overexpressed WT and mutant mcPGK1 transcripts and detected the mitochondrial translocation of PGK1 via Matrix-APEX and OMM-APEX. Overexpression of WT mcPGK1 promoted the mitochondrial translocation of PGK1, whereas HR#2 and HR#7 mutant transcripts had no such effect, further confirming the essential role of HR#2/#7 in mcPGK1-dependent mitochondrial translocation of PGK1 (Fig. 8F).

**Fig. 8: *McPGK1* promotes the mitochondrial entry of PGK1.**

We then examined and found that mcPGK1 knockdown decreased the inactivating phosphorylation of PDH (Fig. 8G). As expected, mcPGK1-PGK1-PDK1 mediated PDH phosphorylation inhibited PDH’s function of converting pyruvate to acetyl-CoA, and subsequently drove a metabolic reprogramming from OXPHOS to glycolysis (Supplementary Fig. 9B). These data confirmed the role of mcPGK1-PGK1-PDK1-PDH axis in metabolism reprogramming from OXPHOS to glycolysis (Supplementary Fig. 9C). Finally we evaluated the role of PGK1-PDK1-PDH axis in mcPGK1 function. Nanoparticle-delivered PGK1 mitochondrial translocation largely diminished the role of mcPGK1 knockdown, indicating that mcPGK1 functions through PGK1 mitochondria-entry (Fig. 8H and Supplementary Fig. 9D). Moreover, mcPGK1 overexpression had a limited role in sphere formation upon PDK1 blockade (Fig. 8I). Similarly, mcPGK1 overexpression also showed impaired roles in sphere formation and in vivo propagation upon PDK1 was silenced, further confirming that mcPGK1 exerted its functions through PDK1-PDH pathway (Supplementary Fig. 9E, F). Taken together, these results indicate that mcPGK1 drives mitochondrial translocation of PGK1, inhibits OXPHOS and promotes glycolysis via the PGK1–PDK1–PDH pathway.

Discussion

In this work, we identified mitochondria-encoded mcPGK1 promotes liver TIC self-renewal via metabolic reprogramming from OXPHOS to glycolysis. McPGK1 interacts with PGK1, promotes the binding of PGK1 to TOM40 mitochondrial importing complex, and drives the mitochondrial translocation of PGK1. Metabolic reprogramming switches the metabolites from α-KG to lactic acid, activates Wnt/β-catenin and liver TIC function. Our work reveals an additional layers to circRNA function, TIC self-renewal and metabolism regulation.

circRNAs, generated by back-splicing of the 3' and 5' ends of RNA, have emerged as critical modulators in a variety of biological processes. With recent advances in RNA sequencing, several new types of circRNAs have been identified, including read-through, virus-encoded, and mitochondria-encoded circRNAs²². Here, we focus on mitochondria-encoded circRNA in liver TICs. Mitochondria contain a copy of circular double-stranded DNA, about 16.5 kb long, from which circRNAs are generated. Very recently, the mitochondria-encoded circRNA SCAR was discovered to alleviate NASH by reducing mROS output²³. Here, we identified TIC-regulatory function of mcPGK1, a newly identified mitochondria-encoded circRNA, adding an additional layer to the function of circRNAs and regulation of TICs.

Mitochondria contain 1000–3000 proteins, most of which are encoded by nuclear genes. The blockade of mitochondrial translocation triggers various disorders, including obesity⁴⁴. Here we revealed that a dysregulated mitochondrial translocation of PGK1 drives liver tumorigenesis, TIC self-renewal and metabolic reprogramming. Because each cell contains many copies of mitochondrial DNA, it is difficult to manipulate the expression of mitochondrial genes, which hinders research aimed at investigating their biological roles. Several studies have revealed that siRNA and shRNA can be used to silence gene expression in mitochondria⁴⁵, and a CRISPR-free mitochondrial base editing system has been created that can change C:G to T:A in mitochondrial DNA in an efficient and specific manner⁴⁶. A mitochondria-targeting nanoparticle has also been constructed and used to deliver genes to mitochondria²³. In this study, we used shRNA to silence mcPGK1 expression. Nuclear overexpression of mcPGK1 was implicated in liver TIC self-renewal and metabolic reprogramming. Indeed, while mcPGK1 is mainly localized to the mitochondria, it is also present in the cytoplasm. We also demonstrated that mcPGK1 was required for the mitochondrial translocation of PGK1, which was normally localized to the cytoplasm.

Mitochondrial metabolism is closely related to stemness regulation. Actually, increased mitochondrial biogenesis and OXPHOS induce the differentiation of various stem cells, indicating that the loss of mitochondrial function is very important for stemness maintenance⁴⁷. Mitochondrial biogenesis, fission and metabolic plasticity are involved in asymmetric division and prostate TIC self-renewal⁴⁸. Some stemness factors, such as Nanog, reduce OXPHOS activity and decrease mROS production to maintain the self-renewal capacity⁴⁹. Here, we revealed that in liver TICs, a highly expressed circRNA drives metabolic reprogramming from OXPHOS to glycolysis by modulating the mitochondrial distribution of PGK1. Metabolic reprogramming from OXPHOS to glycolysis may provide a material basis for the rapid propagation of tumor cells, and the metabolites may also play key roles in the regulation of stemness. Indeed, here we found that lactic acid and α-KG are involved in Wnt/β-catenin activation and liver TIC function.

In addition to TIC self-renewal, metabolic reprogramming contributes to drug resistance and immune escape. The reduction in OXPHOS results in reduced mROS production, promotes a cellular quiescent state, and maintains the genomic stability of stem cells⁵⁰. The reduction in mROS production via metabolic reprogramming in TICs is thought to play a key role in resistance to chemotherapeutic drugs⁵¹. Glycolysis also inhibits anti-tumor immune activity⁵². In particular, TICs increase the production of lactic acid through glycolysis, thus maintaining an acidic tumor microenvironment that inhibits the function of anti-tumor immune cells such as T effector and natural killer cells⁵³. Therefore, the metabolic reprogramming from OXPHOS to glycolysis may inhibit immune surveillance during tumorigenesis. Hence, mcPGK1 might contribute to tumor immune escape and the therapeutic effect of immune checkpoint therapy of liver tumors.

Methods

Ethics statement, mice and cells

This work was approved by the ethics committee of Zhengzhou University (ZZUIRB202054 and ZZUIRB202055). For all mouse experiments, 6-week-old male BALB/c nude mice were purchased were purchased from Beijing Vital River Laboratory Animal Technology Co., Ltd., and housed in the animal facility at School of Life Sciences, Zhengzhou University. Mice were housed in SPF condition, with 4-7 mice per cage in 12 h light/dark cycle (7:00-19:00 light, 19:00-7:00 dark), with controlled room temperature (23 ± 2 °C) and humidity (40-60%). All mice were randomly grouped and no mice were excluded from analyses. The maximal tumor burden over 2500 mm³ is forbidden by the ethics committee, and this limit was not exceeded in all experiments. All efforts to minimize animal suffering were made. Liver cancer tissues used in this work were obtained from The First Affiliated Hospital of Zhengzhou University. Hep3B cells were obtained from ATCC (catalog no, HB-8064), Huh7 cells were obtained from iCellbioscience (catalog no. iCell-h080), 293 T, PLC and Hep-1 cells were from Zusen Fan lab (Institute of Biophysics, Chinese Academy of Sciences).

Antibodies and Reagents

Anti-β-Catenin (catalog no. 610153) and anti-CD133 antibody (catalog no. 566598) was purchased from BD Bioscience. Anti-PGK1 (catalog no. 68540 S), anti-EEA1 (catalog no. 3288 S), anti-β-actin (catalog no. 4970), anti-H3 (catalog no. 4499) and anti-H3K4me3 (catalog no. 9751 S) antibodies were from Cell Signaling Technology. Anti-ZIC2 (catalog no. ARP35821_P050) antibody was purchased from Aviva Systems Biology. Anti-TOM40 (catalog no. 18409-1-AP), anti-TOM70 (catalog no. 14528-1-AP), anti-c-MYC (catalog no. 10828-1-AP) and anti-AXIN2 (catalog no. 20540-1-AP) antibodies were from Proteintech Group, Inc. Goat anti-Mouse IgG (H + L) Cross-Adsorbed Secondary Antibody, Alexa Fluor™ 594 antibody (catalog no. A-11005), Goat anti-Rabbit IgG (H + L) Cross-Adsorbed Secondary Antibody, Alexa Fluor™ 488 (catalog no. A-11008), Goat anti-Rabbit IgG (H + L) Cross-Adsorbed Secondary Antibody, Alexa Fluor™ 647 (catalog no. A-21244) were purchased from Invitrogen. HRP-conjugated Affinipure Goat Anti-Mouse IgG(H + L) antibody (catalog no. SA00001-2) and HRP-conjugated Affinipure Goat Anti-Rabbit IgG(H + L) antibody (catalog no. SA00001-2) were purchased from Proteintech Group, Inc. Polymer HRP and AP detection kits were from Beyotime Biotechnology. Biotin labeled RNA mix (catalog no. 11685597910) was from Roche.

Tumor initiation assay

For tumor initiation assay, 10, 1 × 10², 1 × 10³, 1 × 10⁴, and 1 × 10⁵ mcPGK1 knockdown, overexpressing cells were subcutaneously transplantated into 6-week-old male BALB/c nude mice and tumor initiation was detected after 3 months. Online-available Extreme Limiting Dilution Analysis tool (http://bioinf.wehi.edu.au/software/elda/)⁵⁴ was used for TIC ratio calculation.

Sphere formation

For sphere formation, 1000 Huh7 and PLC single cells were cultured in Ultra Low Attachment 6-well plates, and incubated with Dulbecco’s modified Eagle’s medium/F12 (Life Technologies) supplemented with N2, B27, 20 ng/ml EGF and 20 ng/ml bFGF (Millipore) for 2 weeks, sphere initiating ratio = (sphere number)/1000 × 100%. For primary cells, 5000 cells were used for each well, and sphere initiating ratio = (sphere number)/5000 × 100%.

Separation of mitochondria and mitochondrial fractions

mcPGK1 silenced, overexpressing and control cells were harvested for mitochondria isolation. Isolation buffer (225 mM mannitol, 20 mM MOPS, 75 mM sucrose, 1 mM EGTA, 0.1% BSA, pH 7.2) and lysis buffer (100 mM sucrose, 10 mM MOPS, 1 mM EGTA, 0.1% BSA, pH 7.2) were used for mitochondria isolation.

For separation of mitochondrial fractions, mitochondria were incubated with 1 ml digitonin buffer (mitochondria isolation buffer containing 0.5 mg/ml digitonin) for 15 min, followed by 10,000 x g (10 min, 4 °C) centrifuge. The pellet contained mitoplast and the supernatant contained OMM and IMS fractions. Then OMM fraction was obtained from the precipitate of 10,000 x g (30 min, 4 °C) centrifuge. The mitoplast pellet was re-suspended into 0.2 ml mitochondria isolation buffer and gently disrupted with ultrasonication, followed by 10,000 x g (30 min, 4 °C) centrifuge. The IMM fraction was in pellet and matrix fraction was in supernatant.

Absolute quantification of mcPGK1

For absolute quantification, total cells or cell fractions from peri-tumor, tumor, TIC and sphere cells were used for RNA extraction, followed by 1U/mg RNase R treatment at 37 °C for 15 min. RNA samples were then reversely transcribed to cDNA and quantitative real-time PCR was performed. In vitro transcribed mcPGK1 was used for standard curve by series dilution.

APEX submitochondrial fractions

For APEX assay, liver cancer cells were transfected with Matrix-APEX2 (Cat# 72480, Addgene)⁵⁵, IMS-APEX2 (Cat# 79058, Addgene)⁵⁶, or OMM-APEX2 plasmids (Cat# 79056, Addgene)⁵⁵ for submitochondrial labeling. The cells were treated with 500 mM biotin-phenol at 37 °C for 30 min, and then treated with 1 mM H₂O₂ at room temperature for 1 min. Samples were then treated with 2 mL azide-free quenching solution and 5 mM Trolox for 1 min. Streptavidin-conjugated magnetic beads were washed twice with RIPA lysis buffer (150 mM NaCl, 1% NP-40, 0.5% sodium deoxycholate, 0.1% SDS, 1 mM EDTA, 50 mM Tris, pH 8.0), and subjected into whole cell lysate for 2 h incubation. After washing with RIPA buffer four times, beads were boiled for 15 min and subjected into Western blot.

Preparation of Mito-nanoparticle

The mito-nanoparticles were designed and synthesized as discribed^23,57. Mitochondria-targeting peptide was synthesized by CHENPEPTIDE Biotechnology Co Ltd (Nanjing, China). PSiCoR (Cat# 12084, Addgene) was used for shRNA expression, and modified PCDNA4 plasmid was used for mcPGK1 overexpression. The sequence of the mcPGK1 shRNA and overexpression was confirmed by Sanger sequencing.

Lentivirus generation and cell infection

pSiCoR was used for knockdown. Sequences of shRNAs targeting the junction sequence of mcPGK1 were cloned into pSiCoR vector (Cat no. 12084, Addgene). For lentivirus packaging, we transfected 293 T cells with pSiCoR and package plasmids (4 mg pSiCoR vector, 1 mg VSVG, 1 mg RRE and 2 mg RSV-REV were used for 10 cm dish). PLC, Huh7 and HCC primary cells were infected by virus supernatants or PEG5000 (Sigma)-enriched precipitates. mcPGK1 overexpressing cells were established similarly. shRNA sequences for PGK1, PDK1 and PDH used in this study were listed in Supplementary Table 1.

RNA extraction and RT-PCR analyses

Total RNA samples were isolated with TRIzol method. 1 μg RNAs were reverse-transcribed into cDNA and then subjected to quantitative real-time PCR analysis with ABI QuantStudio5 Q5. Relative changes in expression levels were calculated. RT-qPCR primers are listed in Supplementary Table 2.

RNA pulldown

Spheres were crushed with RIPA buffer supplemented with protease inhibitor cocktail and RNase inhibitor, and pre-cleared with streptavidin beads for 1 h. Biotin labeled RNA probes and cell lysis were mixed together in 4 °C for 3 h, and biotin-enriched components were separated and the binding proteins were detected with silver staining or immunoblot.

Silver staining and mass spectrometry analysis

Pulldown samples from spheres by mcPGK1 probes and antisense probes were boiled for 15 min, separated through 15% SDS-PAGE, and observed by sliver staining. The variant bands in mcPGK1 eluate were identified through mass spectrometry analysis (LTQ Orbitrap XL).

Immunoblot

For immunoblot, samples were crushed and boiled in 1×SDS-loading buffer for 15 min, and then proteins were separated by electrophoresis. Proteins were then transferred to nitrate cellulose (NC) membrane, followed by detection with primary antibody and HRP-conjugated antibodies, finally the HRP signals were visualized by ultra-sensitive enhanced chemiluminescent (ECL) substrate⁵⁸.

Northern blot

Total RNA from CD133^high, CD133^low, sphere and non-sphere samples was extracted with standard TRIzol method, separated with electrophoresis and transferred to positively charged NC film (Beyotime Biotechnology), and then cross-linked by UV exposure. RNA samples on NC membranes were detected with digoxin-labeled RNA probes, which were generated through in vitro transcription. Finally RNA signals were detected with HRP-conjugated anti-digoxin antibody.

RNA immunoprecipitation

Spheres were lyzed in RNase-free RIPA buffer supplemented with RNase inhibitor and protease-inhibitor cocktail, centrifuged and supernatants were collected for preclear with Protein A/G. PGK1 and control antibodies were mixed with Protein A/G, followed by 4 h incubation with precleared sphere lysates. Finally RNA samples in eluate were extracted and mcPGK1 enrichment was detected through quantitative real-time PCR.

Signaling pathway activity reporter system

Wnt/β-catenin, Notch, Hedgehog, mTOR, NF-kB, P38, JNK, ERK and PKA reporter plasmids were overexpressed liver cancer cells, and treated with lactic acid or DM-αKG⁵⁹. The activity levels of each signaling pathway were detected by FACS. For example, Wnt activity level = (TOP-GFP intensity)/(FOP-GFP intensity). The plasmids used in this assay are: TOP-GFP (addgene no. 35489), FOP-GFP (addgene no. 35490), 12XCSL-d1EGFP (addgene no. 47684), 7Gli:GFP (addgene no.110494), TORCAR (addgene no. 64927), NF-kB-eGFP (addgene no. 118093), TORCAR(T/A) (addgene no. 64928), p38KTRmCerulean3 (addgene no. 59155), JNKKTRmRuby2 (addgene no. 59154), PKAKTRClover (addgene no.59153), ERKKTRClover (addgene no. 59150).

Reporting summary

Further information on research design is available in the Nature Portfolio Reporting Summary linked to this article.

Data availability

The circRNA sequencing data generated in this study have been deposited in the Gene Expression Omnibus (GEO) Database under accession code GSE223661. Source data generated in this study are provided in the Source Data file. Source data are provided with this paper.

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Acknowledgements

This work was supported by Ministry of Science and Technology of China (2020YFA0803501 to P.Z.), National Natural Science Foundation of China (82273478, U1704174 and 81872411 to Z.C., 82173176 to P.Z.), Program for Innovative Talents of Science and Technology in Henan Province (18HASTIT042 to Z.C.), Young Talent Support Project from Chinese Association of Science and Technology (YESS20170042 to Z.C.), Science Foundation for Excellent Young Scholars in Henan (202300410358 to Z.C.). Young Talent Support Project from Henan province (2018HYTP002 to Z.C.). We thank the supporting grants from Zhengzhou University to P.Z., and the technical support from Modern Analysis and Computer Center of Zhengzhou University.

Author information

These authors contributed equally: Zhenzhen Chen, Qiankun He, Tiankun Lu, Jiayi Wu.

Authors and Affiliations

School of Life Sciences, Zhengzhou University, 100 Kexue Road, Zhengzhou, Henan, 450001, China
Zhenzhen Chen, Qiankun He, Tiankun Lu, Gaoli Shi & Pingping Zhu
School of Medicine, Nankai University, 94 Weijin Road, Tianjin, 300071, China
Jiayi Wu
Department of Pathophysiology, School of Basic Medical Sciences, Zhengzhou University, Zhengzhou, Henan, 450001, China
Luyun He
Department of Oncology, The First Affiliated Hospital of Zhengzhou University, NO.1 Eastern Jianshe Road, Zhengzhou, 450052, Henan, China
Hong Zong
Research Center of Basic Medicine, Academy of Medical Sciences, Zhengzhou University, Zhengzhou, Henan, China
Benyu Liu

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Z.C. designed and performed experiments, analyzed data and wrote the paper; Q.H., T.L., J.W., G.S., L.H. and H.Z. performed experiments and analyzed data, B.L. designed experiments, analyzed data and wrote the paper; P.Z. initiated the study, designed and performed experiments, analyzed data and wrote the paper.

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Chen, Z., He, Q., Lu, T. et al. mcPGK1-dependent mitochondrial import of PGK1 promotes metabolic reprogramming and self-renewal of liver TICs. Nat Commun 14, 1121 (2023). https://doi.org/10.1038/s41467-023-36651-5

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Received: 27 January 2021
Accepted: 10 February 2023
Published: 27 February 2023
DOI: https://doi.org/10.1038/s41467-023-36651-5

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