Graphical abstract

   graphic file with name fx1.jpg
   [49]Open in a new tab

Highlights

     * •
       Asparagine starvation reduces iron import by downregulating the
       TFRC
     * •
       Iron-dependent histone demethylation is suppressed by asparagine
       starvation
     * •
       IREB2 is responsible for the mRNA expression of TFRC during
       asparagine starvation
     * •
       Metabolic adaptive genes are activated by H3K4 tri-methylation
       during starvation
     __________________________________________________________________

   Biological sciences; Physiology; Molecular biology; Molecular mechanism
   of gene regulation; Epigenetics

Introduction

   Mammalian cells respond to amino acid starvation through
   transcriptional and translational regulation to dictate cell
   fate.[50]^1^,[51]^2 Recent work suggests that amino acid restriction
   can also modulate gene expression through altering epigenetic
   modifications on DNA and histone, thereby impacting cell fate
   decision.[52]^3^,[53]^4 For example, short-term methionine restriction
   poises inducible pluripotent stem cells for differentiation by reducing
   intracellular levels of S-adenosylmethionine (SAM), which is derived
   from methionine and is an indispensable substrate for DNA and histone
   methyltransferase.[54]^5 Similarly, studies in multiple mammalian cell
   systems show that α-ketoglutarate (α-KG) is a key substrate for DNA and
   histone demethylases.[55]^6^,[56]^7^,[57]^8^,[58]^9^,[59]^10^,[60]^11
   Since intracellular α-KG can be maintained through the metabolism of
   several amino acids, including glutamine, serine, and branch-chained
   amino acids, manipulating their availability can profoundly affect cell
   fate decision through modulating histone and DNA demethylation.

   Unlike the other proteinogenic amino acids, asparagine is the only one
   that has not been found to be able to be catabolized in mammalian
   cells,[61]^12 and thus whether its availability can contribute to
   histone methylation or demethylation has not been studied. Using human
   leukemic cells that are auxotrophic for asparagine as a model, we
   reported that asparagine starvation led to an increase in several
   histone methylation markers. This increase was neither due to the
   change of expression of histone-modifying enzymes nor due to the
   alteration of intracellular SAM or α-KG. Instead, asparagine starvation
   reduces the intracellular pool of labile iron (Fe^2+), an indispensable
   co-factor for the Jumonji family of histone demethylases (JHDMs), and
   therefore suppresses histone demethylation. We demonstrate that
   asparagine starvation suppresses the expression of iron-responsive
   element-binding protein 2 (IREB2), an iron-sensing protein,[62]^13 to
   reduce the mRNA expression of the transferrin receptor (TFRC), a major
   carrier for iron uptake.[63]^14 Furthermore, iron supplementation under
   conditions of asparagine starvation restored histone demethylation and
   altered gene expression to accelerate cell death. Taken together, our
   results identified that regulation of iron-dependent histone
   demethylation is part of the metabolic adaptation during asparagine
   starvation.

Results

Asparagine starvation leads to an increase of histone methylation

   To determine the impact of asparagine availability on histone
   methylation status, we withdraw asparagine from the culture medium in
   four acute lymphoblastic leukemia (ALL) cell lines. We found that
   depletion of exogenous asparagine for 24–48 h caused a global increase
   of tri-methylation of histone H3 subunit at multiple lysine residues,
   including K27, K4, and K9 ([64]Figures 1A and [65]S1A), in RS4; 11 and
   DND-41 cells that do not express asparagine synthetase (ASNS)
   ([66]Figure 1B). There was no change of these markers in SEMK2 and
   Jurkat cells that express high levels of ASNS ([67]Figures 1A and 1B).
   We also did not observe any change of di-methylation at H3K4 residue in
   all these four cell lines ([68]Figure 1A). Overexpression of ASNS in
   RS4; 11 cells prevented the increase of H3K27me3, H3K4me3, and
   H3K9me2/3 following asparagine depletion ([69]Figure 1C), while ASNS
   deletion in Jurkat cells induced these 3 markers when exogenous
   asparagine was removed ([70]Figure 1D). These results suggest that the
   inability to maintain asparagine availability is the trigger of the
   global increase of histone H3 methylation.

Figure 1.

   [71]Figure 1
   [72]Open in a new tab

   Asparagine starvation suppresses histone demethylation

   (A) RS4; 11, DND-41, SEMK2, and Jurkat cells were subjected to
   asparagine depletion for 24 h. Cellular expression of H3K27me3,
   H3K4me3, H3K9me2/3, and H3K4me2 was determined by Western blotting.

   (B) The expression of ASNS protein was determined by Western blotting
   in RS4; 11, DND-41, SEMK2, and Jurkat cells.

   (C) ASNS was overexpressed in RS4; 11 cells through lentivirus-mediated
   transduction. Control or ASNS-transduced cells were subjected to
   asparagine depletion for 24 h. The expression of H3K27me3, H3K4me3,
   H3K9me2/3, and H3K4me2 was determined by Western blotting.

   (D) ASNS gene was deleted in Jurkat by CRISPR. Control or ASNS-deleted
   Jurkat cells were subjected to asparagine depletion for 24 h. The
   expression of H3K27me3, H3K4me3, H3K9me2/3, and H3K4me2 was determined
   by Western blotting.

   (E) RS4; 11 cells were subjected to asparagine or glutamine depletion
   for 24 h. Intracellular levels of α-ketoglutarate (α-KG) and
   S-adenosylmethionine (SAM) were determined by quantitative LC-MS.

   (F) RS4; 11 cells were subjected to asparagine or glutamine depletion
   for 24 h with or without 2 mM Dimethyl-α-ketoglutarate (Dm-α-KG). The
   expression of H3K27me3, H3K4me3, H3K9me2/3, and H3K4me2 was determined
   by Western blotting.

   (G) RS4; 11, DND-41, and Jurkat cells were subjected to the treatment
   for 24 h and then stained with BioTracker Far-Red for Fe^2+ detection
   by FACS. DFO was added at 100 μM in the presence of asparagine as a
   control.

   (H) Quantification of the mean fluorescence intensity (MFI) of the
   BioTracker Far-Red staining in the panel (G).

   (I) RS4; 11 and DND-41 cells were treated with 100 μM DFO in the
   presence of asparagine for 24 h. The expression of H3K27me3, H3K4me3,
   H3K9me2/3, and H3K4me2 was determined by Western blotting.

   (J) RS4; 11 and DND-41 cells were subjected to asparagine depletion for
   24 h. Hinokitiol (0.75 μM) with or without Fe(NO[3])[3] (10 μM) was
   added and the MFI of BioTracker Far-Red was determined by FACS.

   (K) RS4; 11 and DND-41 cells were treated as panel (J). The expression
   of H3K27me3, H3K4me3, H3K9me2/3, and H3K4me2 was determined by Western
   blotting. Results in panels E, H, and J were shown as mean ± SD
   (standard derivation). p values were determined by using Student’s
   two-tailed unpaired t-test. See also [73]Figure S1.

   Since amino acid metabolism can affect intracellular levels of SAM and
   α-KG, we performed quantitative liquid chromatography mass spectrometry
   (LC-MS) to measure α-KG and SAM. We found that asparagine starvation
   reduced α-KG to ∼40%, while glutamine starvation nearly depleted
   intracellular α-KG ([74]Figure 1E). In addition, asparagine starvation
   neither increased intracellular SAM or 2-hydroxylglutarate levels nor
   altered the ratio of α-KG/succinate or SAM/SAH
   (S-adenosyl-homocysteine) ([75]Figures 1E, [76]S1B and S1C). To
   determine whether the reduction of α-KG by asparagine starvation causes
   increased histone H3 methylation, we supplemented cells with a
   cell-permeable α-KG (Dm-α-KG). We found that Dm-α-KG supplementation
   reduced H3K27me3, H3K4me3, and H3K9me2/3 under glutamine starvation,
   but not under asparagine starvation ([77]Figure 1F), suggesting the
   reduction of α-KG by asparagine starvation is not the cause of
   increased histone H3 methylation. In addition, we found no correlative
   changes in the expression of histone methyltransferases or demethylases
   that could consistently explain the change of these 3 markers during
   asparagine starvation ([78]Figure S1D).

Asparagine starvation reduces the intracellular pool of labile iron (Fe^2+)
and thereby suppresses histone demethylation

   To determine whether histone methyltransferases contributed to the
   increase of H3 lysine methylation during asparagine starvation, we
   treated RS4; 11 cells with an inhibitor of EZH2 (GSK126),[79]^15 a
   known H3K27 methyltransferase. We found that GSK126 was not as
   effective in reducing the H3K27me3 in the asparagine-depleted
   conditions, suggesting compromised demethylase activities during
   asparagine starvation ([80]Figure S1E). Since the demethylation of
   H3K27me3, H3K4me3, and H3K9me2/3 requires JHDMs that also use Fe^2+ as
   a co-factor, we measured intracellular Fe^2+ levels using BioTracker
   Far-red, a dye specific for ferrous.[81]^16 We used deferoxamine (DFO),
   an iron chelator, to treat the cells in the complete medium as a
   negative control. We found that asparagine starvation for 24 h reduced
   Fe^2+ content to less than 50% in RS4; 11 and DND-41 cells, but not in
   Jurkat cells ([82]Figures 1G and 1H). Consistent with the
   literature,[83]^17 DFO treatment induced H3K27me3, H3K4me3, and
   H3K9me2/3 in RS4; 11 and DND-41 cells, with no impact on H3K4me2
   ([84]Figure 1I). Since demethylation of H3K4me2 uses LSD1/2, two
   lysine-specific demethylases that do not use iron as a
   co-factor,[85]^18 our results are consistent with the hypothesis that
   the global increase of histone H3 methylation under asparagine
   starvation is due to a defect of iron-dependent histone demethylation.
   To determine whether the reduction of intracellular Fe^2+ is necessary
   for the increase of histone H3 methylation, we treated RS4; 11 and
   DND-41 cells with Fe^3+ in the presence of Hinokitiol, a chemical
   carrier for iron import.[86]^19 We found that Fe^3+ plus Hinokitiol,
   but not Hinokitiol alone, restored intracellular Fe^2+ content and
   histone H3 demethylation ([87]Figures 1J and 1K). Furthermore, the
   reduction of H3K27me3 relies on demethylase activities as GSKJ4, an
   inhibitor of the H3K27 demethylases,[88]^20 prevented this effect
   following iron supplementation ([89]Figure S1F).

Asparagine starvation reduces the cell surface expression of the transferrin
receptor (TFRC)

   To determine the cause of the reduction of intracellular Fe^2+ pool, we
   analyzed published RNA-seq data from RS4; 11 cells subjected to
   asparagine starvation[90]^21 and found reduced expression of iron
   homeostatic genes ([91]Figures 2A and 2B). We confirmed the reduction
   of the mRNAs of TFRC, STEAP3, SFXN2, and SLC46A1 ([92]Figure S2A),
   whose major roles are iron uptake and intracellular transport.
   Consistently, both total cellular expression and cell surface
   expression of TFRC, also known as CD71, were reduced by asparagine
   starvation in RS4; 11 and DND-41 cells, but not in SEMK2 and Jurkat
   cells ([93]Figures 2C–2E). Furthermore, ASNS overexpression restored
   TFRC cell surface expression in RS4; 11 cells when asparagine was
   withdrawn, while ASNS deletion in Jurkat cells reduced TFRC cell
   surface expression under the same condition ([94]Figures S2B and S2C).
   Since TFRC is a major carrier for iron uptake,[95]^14 we hypothesize
   that the reduction of TFRC expression by asparagine starvation leads to
   the reduction of intracellular Fe^2+ to suppress iron-dependent histone
   demethylation. To test this hypothesis, we used doxycycline-inducible
   short hairpin RNA (shRNA) to suppress TFRC expression ([96]Figures 2F
   and [97]S2D) and found that doxycycline treatment induced H3K27me3 and
   H3K4me3 in the presence of exogenous asparagine ([98]Figure 2G). This
   induction was mitigated by iron supplementation in the presence of
   Hinokitiol ([99]Figure 2G), which correlated with intracellular Fe^2+
   content ([100]Figure S2E). Conversely, TFRC overexpression in RS4; 11
   and DND-41 cells restored cell surface expression of TFRC,
   intracellular Fe^2+ content, and partially rescued histone
   demethylation under asparagine depletion ([101]Figures S2F, S2G, and
   [102]2H). These results suggest that TFRC is both necessary and
   sufficient for iron-dependent histone demethylation.

Figure 2.

   [103]Figure 2
   [104]Open in a new tab

   Asparagine starvation reduces intracellular iron content by
   downregulating the transferrin receptor (TFRC/CD71)

   (A) Gene set enrichment analysis identified downregulation of mRNAs of
   iron metabolism genes in RS4; 11 cells following asparagine depletion
   for 24 h.

   (B) Heatmap illustration of the change of expression of iron metabolism
   genes in panel (A).

   (C) RS4; 11, DND-41, SEMK2, and Jurkat cells were subjected to
   asparagine depletion for 24 h. TFRC protein expression was determined
   by Western blotting.

   (D) RS4; 11, DND-41, SEMK2, and Jurkat cells were subjected to
   asparagine depletion for 24 h. Cell surface expression of TFRC/CD71 was
   determined by FACS analysis.

   (E) The MFI of cell surface staining of TFRC/CD71 in panel (D) was
   quantified. Results were shown as mean ± SD (standard derivation). p
   values were determined by using Student’s two-tailed unpaired t-test.

   (F) The expression of TFRC in RS4; 11 cells was suppressed by
   doxycycline-inducible shRNA following 48 h of doxycycline (1 μg/mL)
   treatment.

   (G) RS4; 11 cells with control or TFRC shRNA were treated with
   doxycycline for 48 h with or without Hinokitiol (0.75 μM) plus
   Fe(NO[3])[3] (10 μM). The expression of H3K27me3, H3K4me3, H3K9me2/3,
   and H3K4me2 was determined by Western blotting.

   (H) TFRC cDNA was introduced into RS4; 11 and DND-41 via
   lentivirus-mediated gene transduction. Control or TFRC-transduced cells
   were subjected to asparagine depletion for 24 h. The expression of
   H3K27me3, H3K4me3, H3K9me2/3, and H3K4me2 was determined by Western
   blotting. See also [105]Figure S2.

Downregulation of IREB2 is responsible for the reduction of TFRC expression
following asparagine depletion

   The stability of TFRC mRNA is tightly regulated by iron-sensing
   proteins. ACO1 and IREB2 are the two known iron-sensing proteins that
   bind to the iron-responsive elements (IREs) within the 3′ UTR of TFRC
   mRNA to increase its stability when the intracellular iron content is
   low.[106]^13 Elevated cellular iron inactivates ACO1 and IREB2 via
   different molecular machinery to cause their dissociation from TFRC
   mRNA, leading to its degradation and therefore providing a feedback
   mechanism to maintain iron homeostasis. We found that, unlike TFRC, the
   mRNA levels of ACO1 and IREB2 did not change following asparagine
   depletion in both RS4; 11 and DND-41 cells ([107]Figure 3A). However,
   the protein expression of IREB2 was consistently reduced by asparagine
   starvation in RS4; 11 and DND-41 cells, but not in SEMK2 and Jurkat
   cells ([108]Figure 3B). Similarly, only the IREB2 protein, but not
   ACO1, was reduced by asparagine starvation in Jurkat cells lacking ASNS
   gene ([109]Figure 3C). Using the doxycycline-inducible shRNAs, we found
   that only suppression of IREB2 reduced the expression of TFRC at both
   mRNA and protein levels ([110]Figures S3, [111]3D, and 3E).

Figure 3.

   [112]Figure 3
   [113]Open in a new tab

   Asparagine starvation downregulates the expression of IREB2
   post-transcriptionally

   (A) The mRNA expression of TFRC, ACO1, and IREB2 was determined by qPCR
   in RS4; 11 and DND-41 cells following 24-h asparagine depletion.

   (B) RS4; 11, DND-41, SEMK2, and Jurkat cells were subjected to
   asparagine depletion for 24 h. The expression of TFRC, ACO1, and IREB2
   protein was determined by Western blotting.

   (C) Control or ASNS-deleted Jurkat cells were subjected to asparagine
   depletion for 24 h. The expression of TFRC, ACO1, and IREB2 protein was
   determined by Western blotting.

   (D) RS4; 11 cells were transduced with two inducible hairpins of ACO1
   and then treated with doxycycline (1 μg/mL) for 48 h. The expression of
   ACO1 and TFRC protein was determined by Western blotting.

   (E) RS4; 11 cells were transduced with two inducible hairpins of IREB2
   and then treated with doxycycline (1 μg/mL) for 48 h. The expression of
   IREB2 and TFRC protein was determined by Western blotting. See also
   [114]Figure S3.

Asparagine starvation increases H3K4me3 deposition to alter gene expression
and dictate cell fate

   Since histone methylation profoundly affects gene expression, we
   hypothesize that increased H3 lysine methylation under asparagine
   starvation modulates gene expression to mitigate stress. Using H3K4me3
   ChIP-seq, we found a global increase in its deposition across the
   genome following asparagine depletion ([115]Figure S4A). The enrichment
   of H3K4me3 on gene promoters was positively correlated with gene
   expression, consistent with the known role of H3K4me3 on
   transcriptional activation ([116]Figure S4B). Furthermore,
   supplementation of Fe^3+ in the presence of Hinokitiol reduced the
   H3K4me3 deposition in the promoter regions of a portion of genes whose
   H3K4me3 deposition increased in the promoter regions under asparagine
   starvation ([117]Figure S4C). There was a weak correlation between the
   reduction of H3K4me3 deposition and gene expression alteration
   ([118]Figure S4C).

   The genes with increased mRNA expression or increased H3K4me3
   deposition upon asparagine starvation were significantly enriched in
   the cell periphery, plasma membrane synapse, and vesicle trafficking
   given either ChIP-seq ([119]Figure 4A) or RNA-seq results
   ([120]Figure 4B), indicating a potential enhancement of exchanging with
   the extracellular environment. For example, genes in the cytoplasmic
   vesicle membrane pathway were induced by asparagine starvation
   ([121]Figure 4C). The functions of these genes are broadly linked to
   membrane internalization, endocytosis, and endosomal function, which
   can facilitate the utilization of extracellular protein as a source of
   amino acid to mitigate the stress.[122]^22 In addition, Fe^3+
   supplementation suppressed the induction of some of these genes
   involved in cell surface receptor recycling or vesicle trafficking,
   such as SLA and FGD2[123]^23^,[124]^24 ([125]Figure 4D, left panel).
   Furthermore, the mRNA expression of SLA and FGD2 positively correlated
   with H3K4me3 deposition in their promoter regions under these three
   conditions ([126]Figure 4D, right panel).

Figure 4.

   [127]Figure 4
   [128]Open in a new tab

   Asparagine starvation leads to an increase of H3K4me3 deposition to
   modulate gene expression

   (A) RS4; 11 cells were starved for asparagine for 24 h. H3K4me3
   ChIP-seq analysis was performed (n = 3). The differential expression
   peaks (FDR<0.05, |log2FC|>0.25) were subjected to gene ontology and
   pathway functional analysis by using DAVID.

   (B) RS4; 11 cells were starved for asparagine for 24 h. RNA-seq
   analysis was performed (n = 3). The differential expression genes
   (FDR<0.05, |log2FC|>0.25) were subjected to gene ontology and pathway
   functional analysis by using DAVID.

   (C) RS4; 11 cells were starved for asparagine for 24 h. RNA-seq
   analysis was performed (n = 3). A heatmap of the genes in the
   cytoplasmic vesicle membrane pathway was shown.

   (D) RS4; 11 cells were subjected to asparagine starvation with or
   without Fe^3+ supplementation for 24 h. RNA was harvested and the
   relative expression of SLA and FGD2 were determined by qPCR (left).
   H3K4me3 ChIP-seq analysis was performed under the same conditions and
   relative enrichment of H3K4me3 around gene promoters was illustrated by
   the genome browser (right). The result is a merged peak of 3
   replicates.

   (E) RS4; 11 cells were subjected to asparagine starvation for 24 h in
   the presence of other treatments as shown in the legend. Cell death
   index was measured by Annexin V staining.

   (F) RS4; 11 and DND-41 cells were cultured in asparagine-replete or
   -deficient media for 24 h. Pitstop (50 μM) or EIPA (25 μM) was added in
   both conditions. Cell death index was measured by trypan blue staining.
   Results in panels E and F were shown as mean ± SD (standard
   derivation). p values were determined by using Student’s two-tailed
   unpaired t-test. See also [129]Figure S4.

   Previous work from our lab showed that long-term asparagine starvation
   triggered apoptosis, while short-term (<24 h) asparagine starvation
   induced growth arrest with minimal cell death.[130]^25 Thus, we
   hypothesize that cells may uptake extracellular proteins as a means to
   regenerate intracellular amino acids to transiently mitigate asparagine
   starvation. Consistent with this hypothesis, Fe^3+ supplementation
   enhanced cell death within 24 h following asparagine withdrawal
   ([131]Figure 4E). The enhanced cell death is not due to
   ferroptosis,[132]^26 as we did not observe significantly increased
   reactive oxygen species or lipid peroxide ([133]Figures S4D and S4E).
   Furthermore, Q-VD, a pan-caspase inhibitor, suppressed the enhanced
   cell death triggered by Fe^3+ supplementation ([134]Figure 4E). To
   examine our hypothesis, we treated RS4; 11 and DND-41 cells with
   inhibitors of endocytosis (Pitstop 2) or macropinocytosis (EIPA). The
   results showed an enhanced cell death under asparagine starvation
   ([135]Figure 4F).

Discussion

   We conclude that asparagine starvation in asparagine auxotrophic cells
   inhibits the expression of TFRC and thus suppresses iron uptake and
   iron-dependent histone demethylation. Iron supplementation can restore
   histone demethylation and therefore alter gene expression under
   asparagine starvation. Our results indicate that inhibition of histone
   demethylation is part of the metabolic adaptive response to ensure
   proper gene expression to mitigate the stress, as iron supplementation
   accelerates cell death under asparagine starvation. We identified that
   downregulation of IREB2 is a key molecular component to be responsible
   for asparagine starvation-induced inhibition of TFRC expression.
   However, the mechanism underlying the post-transcriptional inhibition
   of IREB2 expression by asparagine starvation remains to be determined.
   For example, FBXL5 is a known E3 ubiquitin ligase of
   IREB2,[136]^27^,[137]^28 whether its activity is regulated by
   asparagine starvation warrants further investigation. Since the
   connection between amino acid restriction and epigenetic regulation
   only comes to focus recently,[138]^29^,[139]^30 our study will provide
   a comprehensive understanding of nutrient availability and histone
   modifications. Furthermore, the dynamic change of TFRC/CD71 expression
   in a variety of physiological and pathological conditions may indicate
   a requirement for iron-dependent histone demethylation to regulate
   epigenome.[140]^31^,[141]^32 Therefore, our results uncover that iron
   homeostasis is another layer of control between amino acid restriction,
   epigenome, and cell fate decision.

Limitations of the study

   This study was restricted to in vitro cell culture system. In addition,
   the phenotype is specific to cells expressing low levels of ASNS. Thus,
   it is important to determine whether our findings contribute to the
   phenotype when ALL cells are treated with L-asparaginase in vivo.
   Furthermore, it is still unclear whether the reduction of intracellular
   iron content is specific to asparagine starvation or can be responsive
   to other nutrient restriction or stress conditions. Finally, JHDMs use
   ferrous (Fe^2+) as a co-factor and our iron detection method can only
   detect ferrous. Since TFRC-mediated iron import is through
   transferrin-bound ferric (Fe^3+), it remains to be determined that
   whether ferric reduction to ferrous is also regulated by amino acid
   starvation. These questions imply that mammalian cells may regulate
   iron homeostasis at multiple layers during amino acid starvation to
   ensure proper iron-dependent metabolic activities to mitigate nutrient
   stress for cellular adaptation.

STAR★Methods

Key resources table

   REAGENT or RESOURCE SOURCE IDENTIFIER
   Antibodies
     __________________________________________________________________

   Rabbit polyclonal α-ASNS ProteinTech Cat. # 14681-1-AP; RRID:
   AB_2060119
   Rabbit monoclonal α-TFRC/CD71 Cell Signaling Technology Cat. # 13208S;
   RRID: AB_2798150
   APC α-TFRC/CD71 (Flow Cytometry) BioLegend Cat. # 334108; RRID
   AB_10915138
   Rabbit polyclonal α-ACO1 ProteinTech Cat. # 12406-1-AP; RRID:
   AB_10642942
   Rabbit monoclonal α-IREB2 Cell Signaling Technology Cat. # 37135S;
   RRID: AB_2799110
   Rabbit monoclonal α-Tri-Methyl-Histone H3 (K27) Cell Signaling
   Technology Cat. # 9733T; RRID: AB_2616029
   Rabbit polyclonal α-Tri-Methyl-Histone H3 (K4) Cell Signaling
   Technology Cat. # 9727S; RRID: AB_561095
   Rabbit polyclonal α-Tri-Methyl-Histone H3 (K4) (ChIP) Active Motif Cat.
   # 39016
   Rabbit monoclonal α-Di-Methyl-Histone H3 (K4) Cell Signaling Technology
   Cat. # 9725S; RRID: AB_10205451
   Mouse monoclonal α-Di/Tri-Methyl-Histone H3 (K9) Cell Signaling
   Technology Cat. # 5327T; RRID: AB_10695295
   Rabbit polyclonal α-Histone H3 ProteinTech Cat. # 17168-1-AP; RRID:
   AB_2716755
   Mouse monoclonal α-MLL Santa Cruz BioTech Cat. # sc-377274; RRID:
   AB_2616342
   Mouse monoclonal α-EZH2 Santa Cruz BioTech Cat. # sc-515817
   Mouse monoclonal α-EZH1 Santa Cruz BioTech Cat. # sc-166609; RRID:
   AB_2246791
   Mouse monoclonal α-KDM6A Santa Cruz BioTech Cat. # sc-514859
   Rabbit polyclonal α-KDM5A ABclonal Technology Cat. # A7238; RRID:
   AB_2767786
   Mouse monoclonal α-β-actin (clone AC-74) Sigma-Aldrich Cat. # A2228;
   RRID: AB_476697
   Mouse monoclonal α-α-tubulin (clone DM-1A) Sigma-Aldrich Cat. # T9026;
   RRID: AB_477593
     __________________________________________________________________

   Chemicals, peptides, and recombinant proteins
     __________________________________________________________________

   Dimethyl alpha-ketoglutarate Sigma Cat. # 349631
   Iron (Fe^3+) nitrate nonahydrate Sigma Cat. # F8508
   Deferoxamine mesylate salt Sigma Cat. # D9533
   Hinokitiol Sigma Cat. # 469521
   doxycycline hydrochloride Sigma Cat. # D3447
   Q-VD-OPH SelleckChem Cat. # S7311
   GSK126 SelleckChem Cat. # S7061
   GSKJ4 SelleckChem Cat. # S7070
   Pitstop 2 MedChemExpress Cat. # HY-115604
   EIPA MedChemExpress Cat. # HY-101840
   BioTracker Far-Red Labile Fe^2+ dye Millipore Sigma Cat. # SCT037
   Fixable viability dye eFluor 450 eBioscience Cat. # 65-0863-14
   H2DCFDA ROS dye Thermo Fisher Scientific Cat. # D399
   LiperFluo Dojindo Molecular Technologies Cat. # [142]L24810
   Erastin SelleckChem Cat. # S7242
   Tert-Butyl hydroperoxide (t-BHP) Thermo Fisher Scientific Cat. #
   AC180340050
     __________________________________________________________________

   Deposited data
     __________________________________________________________________

   RNA seq of leukemia cells following asparagine depletion Jiang
   et al.[143]^21 GEO: [144]GSE135420
   RNA seq of leukemia cells (RS4;11) following asparagine depletion This
   paper GEO: [145]GSE206112
   H3K4me3 ChIP seq of leukemia cells (RS4;11) following asparagine
   depletion This paper GEO: [146]GSE206112
     __________________________________________________________________

   Experimental models: Cell lines
     __________________________________________________________________

   RS4;11 ATCC ATCC® CRL-1873™; RRID: CVCL_0093
   RS4;11 (control and ASNS overexpressing cells) Jiang et al.[147]^21 NA
   SEMK2 Ross Levine, MSKCC RRID: CVCL_S906
   Jurkat ATCC ATCC® TIB-152™; RRID: CVCL_0065
   Jurkat (control and ASNS knockout cells) Srivastava et al.[148]^25 NA
   DND-41 Hui Feng, Boston University RRID: CVCL_2022
   DND-41 (control and ASNS overexpressing cells) Jiang et al.[149]^21 NA
     __________________________________________________________________

   Oligonucleotides
     __________________________________________________________________

   RT-PCR primers See [150]Table S1 NA
   sgGFP guide RNA sequence GTGAACCGCATCGAGCTGAA IDT DNA NA
   sgASNS guide RNA sequence
   TTGTCATAGAGGGCGTGCAG IDT DNA NA
   shCtrl hairpin RNA sequence
   CAGGAATTATAATGCTTATCTA IDT DNA NA
   shTFRC hairpin RNA sequence
   AGGTGATCATAGTTGATAAG IDT DNA NA
   shACO1-1 hairpin RNA sequence
   CGGCAACGATATAAGTACAT IDT DNA NA
   shACO1-2 hairpin RNA sequence
   CCCACAGGATACTCTTGAGA IDT DNA NA
   shIREB2 -1 hairpin RNA sequence
   CTCAGACCATTTTGTAAATA IDT DNA NA
   shIREB2 -2 hairpin RNA sequence
   CGAGTAGCAGATTGAAATAT IDT DNA NA
     __________________________________________________________________

   Recombinant DNA
     __________________________________________________________________

   Lenti-CRISPRv2-Puro-sgCtrl[151]^33 Addgene (Deposited by Brett
   Stringer) Addgene #98290; RRID: Addgene_98290
   Lenti-CRISPRv2-Puro-sgASNS Addgene backbone #98290 Addgene #98290;
   RRID: Addgene_98290
   LeGO-iG2[152]^34 Addgene (Deposited by Boris Fehse) Addgene #27341;
   RRID: Addgene_27341
   LeGO-ASNS-iG2 (ASNS cDNA purchased from Dharmacon) Addgene backbone
   #27341 Addgene #27341; RRID: Addgene_27341
   Second-generation lentiviral vector expressing EGFP and puromycin
   resistant gene[153]^35 Layer et al.[154]^35 (Shared by Utpal Dave) NA
   Second-generation lentiviral vector expressing EGFP and puromycin
   resistant gene, containing TFRC cDNA Layer et al.[155]^35 (Shared by
   Utpal Dave) NA
   LT3GEPIR-shCtrl[156]^36 Addgene (Deposited by Johannes Zuber) Addgene
   #111177; RRID: Addgene_111177
   LT3GEPIR-shTFRC Addgene backbone #111177 Addgene #111177; RRID:
   Addgene_111177
   LT3GEPIR-shACO1 Addgene backbone #111177 Addgene #111177; RRID:
   Addgene_111177
   LT3GEPIR-shIREB2 Addgene backbone #111177 Addgene #111177; RRID:
   Addgene_111177
   pMD2.G VSV-G envelope plasmid Addgene (Deposited by Didier Trono)
   Addgene #12259; RRID: Addgene_12259
     __________________________________________________________________

   Software and algorithms
     __________________________________________________________________

   Maven[157]^37^,[158]^38 Melamud et al.; Clasquin
   et al.[159]^37^,[160]^38 [161]http://maven.princeton.edu/index.php;
   RRID:SCR_022491
   STAR (v2.7.2a)[162]^39 Dobin et al.[163]^39
   [164]http://code.google.com/p/rna-star/; RRID:SCR_004463
   featureCounts (v1.6.2)[165]^40 Liao et al.[166]^40
   [167]http://bioinf.wehi.edu.au/featureCounts/; RRID:SCR_012919
   edgeR (v3.36.0)[168]^41 McCarthy et al.; Robinson
   et al.[169]^41^,[170]^42 [171]http://bioconductor.org/packages/edgeR/;
   RRID:SCR_012802
   DAVID[172]^43^,[173]^44 Dennis et al.; Huang da
   et al.[174]^43^,[175]^44 [176]https://david.ncifcrf.gov/;
   RRID:SCR_001881
   MsigDB (v6)[177]^45 Subramanian et al.[178]^45
   [179]http://software.broadinstitute.org/gsea/msigdb/index.jsp;
   RRID:SCR_016863
   Bowtie2[180]^46 Langmead and Salzberg,[181]^46
   [182]http://bowtie-bio.sourceforge.net/bowtie2/index.shtml;RRID:SCR_016
   368
   Picard NA [183]http://broadinstitute.github.io/picard/; RRID:SCR_006525
   MACS2[184]^47 Zhang et al.[185]^47
   [186]https://github.com/macs3-project/MACS; RRID:SCR_013291
   ENCODE blacklist[187]^48^,[188]^49 Amemiya et al.;
   Consortium,[189]^48^,[190]^49
   [191]https://github.com/Boyle-Lab/Blacklist/
   [192]Open in a new tab

Resource availability

Lead contact

   Further information and requests for resources and reagents should be
   directed to and will be fulfilled by the lead contact, Ji Zhang
   ([193]jzh1@iu.edu).

Material availability

   All reagents will be made available on request after the completion of
   a Material Transfer Agreement.

Experimental model and subject details

Cell culture

   All human leukemic cell lines were cultured at 37°C in 5% CO[2] in a
   lymphocyte culturing medium (LCM). The base of LCM is a 1:1 ratio
   mixture of DMEM and IMDM. For practical reason and quality control
   purpose, we can consistently generate LCM in lab through supplementing
   high glucose DMEM (11965092, Thermo Fisher Scientific) with: 0.14 mM
   L-Alanine, 0.17 mM L-Proline, 5.3 × 10^5 mM Biotin, 9.59 × 10^−5 mM
   Vitamin B12 and 9.8 × 10^−5 mM Sodium Selenite, 10 mM HEPES, and 55 μM
   β-mercaptoethanol, 100 Units/mL penicillin/streptomycin, 2 mM
   L-Glutamine, 10% FBS and 0.1 mM L-Asparagine. For asparagine or
   glutamine starvation, cells were centrifuged and supernatant was
   removed by aspiration. Cell pellets were resuspended in asparagine- or
   glutamine-free LCM. Asparagine- or glutamine-free LCM was made from
   high glucose DMEM lacking glutamine (11960044, Thermo Fisher
   Scientific) as described above, with the exception of using 10%
   dialyzed FBS. Cell viability and viable cell numbers were recorded in
   using the Vi-CellXR cell viability analyzer (Beckman Coulter). When the
   earlier apoptotic marker was measured, we used Annexin V-FITC (BD
   Bioscience, 560931).

Method details

Western blotting

   For non-histone blots, protein was extracted by using 1× RIPA buffer
   (diluted from 10x RIPA lysis buffer, Millipore, Cat. # 20-188) with
   protease inhibitors (Thermo Scientific, Cat. # 1860932) and phosphatase
   inhibitors (Thermo Scientific, Cat. # 78428). For histone blots, cells
   were first lysed with Triton Extraction Buffer (PBS containing 0.5%
   Triton plus protease inhibitors). Nuclei were collected by
   centrifugation and then lysed with 0.2 N HCl overnight at 4°C.
   Supernatant was collected by centrifugation and then neutralized with
   1/10 volume of 2 M NaOH. Total proteins of equal amount (20 μg for
   non-histone and 5 μg for histone) were separated on NuPAGE Bis-Tris
   gels (Invitrogen, Cat. # NP0322BOX) and then transferred to
   Nitrocellulose membranes (Bio-Rad, Cat. # 1620115). Membranes were
   blocked in 5% milk and then incubated with corresponding primary
   antibodies overnight at 4°C. Membranes were washed with 1×Tris Buffered
   Saline with Tween 20/TBST (diluted from 20x TBST, Santa Cruz
   Biotechnology, Cat. # 362311) and then incubated with horseradish
   peroxidase (HRP) conjugated secondary antibody (ECL anti-rabbit IgG,
   Sigma, Cat. # NA934V; ECL anti-mouse IgG, Sigma, Cat. # NA931V. 1:5000
   dilution). Membranes were washed with 1× TBST and subjected to
   Chemiluminescent Western ECL detection (Thermo Scientific, Cat. #
   32106). The blots were stripped with Restore Western Blot Stripping
   Buffer (Thermo Scientific, Cat. # 21059), washed with 1xTBST, and then
   re-probed with appropriate primary antibodies for signal detection.

Mass spectrum analysis of intracellular metabolite

   Cells were collected by centrifugation, supernatant was aspirated and
   the pellets were washed thoroughly once with ice cold 1 × HBSS
   (14025092, Life Technology). Cellular metabolites were extracted with
   80% methanol on ice. Supernatant was collected and dried with SpeedVac
   (SPD111V, Thermo Fisher Scientific) connected to Refrigerated Vapor
   Trap (RVT5105, Thermo Fisher Scientific) at room temperature. Dried
   samples were resuspended in 40:40:20 acetonitrile:MeOH:water and
   analyzed using a Thermo Q-Exactive mass spectrometer coupled to a
   Vanquish Horizon UHPLC. Metabolites were separated on a 150 × 2.1 mm
   Xbridge BEH Amide (2.5 μM) HPLC Column (Waters). Samples were run with
   a gradient of solvent A (95% H[2]O, 5% ACN, 20 mM NH[4]AC, 20 mM
   NH[4]OH) and solvent B (20% H[2]O, 80% ACN, 20 mM NH[4]AC, 20 mM
   NH[4]OH) as follows: 0 min, 100% B; 3 min, 100% B; 3.2 min, 90% B;
   6.2 min, 80% B; 10.5 min, 80% B, 10.7 min, 70% B; 13.5 min, 70% B;
   13.7 min, 45% B; 16 min, 45% B; 16.5 min 100% B; 22 min, 100% B. Data
   were collected on a full scan. Flow rate was 0.2 ml/min. Metabolites
   were identified based on exact M/z and retention time determined using
   chemical standards. Data were analyzed with Maven,[194]^37^,[195]^38
   and normalized to internal standard of ^13C[4],^15N[2]-Asparagine (1
   pmole/sample) and then total cell number of each sample.

Intracellular ferrous (Fe^2+), ROS, and lipid peroxide measurement

   Cells were collected by centrifugation and washed once with PBS.
   BioTracker Far-Red (SCT037, Millipore Sigma) was diluted in serum-free
   DMEM at final concentration of 5 μM. Resuspend 1 million cells in
   100 μL of diluted BioTracker Far-Red staining medium in 96-well plates
   and incubate the plate reaction in 37°C CO[2] incubator for 1 hour.
   Cells with staining medium was further diluted with 400 μL serum-free
   DMEM containing eFluor 450 (65-0863-14, eBioscience) at 1:4000 dilution
   for dead cell labeling. The signal of BioTracker Far-Red was captured
   in RL1 channel by the Invitrogen Attune NxT Flow Cytometer. For the ROS
   measurement, cells were stained in 100 μL serum-free DMEM with
   5 μM H[2]DCFDA (D399, Thermo Fisher Scientific) at 37°C for 30 minutes
   and then diluted with 400 μL serum-free DMEM before detection. The
   signal of H[2]DCFDA was captured in BL1 channel by the Invitrogen
   Attune NxT Flow Cytometer. Lipid peroxide was detected by Liperfluo
   (Dojindo Molecular Technologies, [196]L24810) staining at 1 μM for
   30 minutes prior to Flow Cytometry analysis. We used APC anti-human
   CD71 (334108, BioLegend Inc.) to label cell surface expression of CD71.

Molecular cloning and virus production

   Mouse ASNS cDNA was cloned into the LeGO-iG2 vector backbone for
   overexpression in RS4;11 cells (Addgene, #27341). Human TFRC/CD71 cDNA
   was cloned into a second-generation lentiviral vector expressing EGFP
   and puromycin resistant gene at the same time for
   dual-selection.[197]^35 Guide RNAs for human ASNS gene were designed
   using Feng Zhang lab’s CRISPR design resource:
   [198]http://crispor.tefor.net/ and cloned into pLentiCRISPRv2-Puro
   vector (Addgene, Cat. # 98290). The design of the doxycycline-inducible
   shRNAs targeting human TFRC, ACO1 and IREB2 was previously
   described.[199]^50 The hairpins were cloned into the LT3GEPIR vector
   (Addgene, Cat# 111177).[200]^36 We used pMD2.G (Addgene, Cat# 12259)
   and psPAX2 (Addgene, Cat# 12260) as packaging plasmids for lentiviral
   particle production in 293T cells.

mRNA quantification

   Total RNA was then isolated with TRIzol (15596026, Life Technologies)
   according to the manufacturer’s instructions. 0.5–2 μg total RNA was
   processed for cDNA synthesis with random hexamer primers, using
   EasyScript Plus RTase from the EasyScript Plus cDNA Synthesis Kit
   (Lamda Biotech, Cat. #G235). The synthesized cDNA was then subjected
   for qPCR amplification with designed PCR primers for human target
   genes.

RNA sequencing

   Total RNA was first evaluated for its quantity, and quality, using
   Agilent Bioanalyzer 2100. For RNA quality, a RIN number of 7 or higher
   is desired. One hundred nanograms of total RNA was used. cDNA library
   preparation included mRNA purification/enrichment, RNA fragmentation,
   cDNA synthesis, ligation of index adaptors, and amplification,
   following the KAPA mRNA Hyper Prep Kit Technical Data Sheet, KR1352 –
   v4.17 (Roche Corporate). Each resulting indexed library was quantified
   and its quality accessed by Qubit and Agilent Bioanalyzer, and multiple
   libraries pooled in equal molarity. The pooled libraries were then
   denatured, and neutralized, before loading to NovaSeq 6000 sequencer at
   300pM final concentration for 100b paired-end sequencing (Illumina,
   Inc.). Approximately 30–40M reads per library was generated. A Phred
   quality score (Q score) was used to measure the quality of sequencing.
   More than 90% of the sequencing reads reached Q30 (99.9% base call
   accuracy).

Chromatin immunoprecipitation followed by high throughput sequencing
(ChIP-seq)

   1 × 10^7 cells were resuspended in 25 mL PBS and fixed with 1%
   formaldehyde (final concentration) on a platform rocker at room
   temperature for 10 min 1.4 mL of 2.5M glycine was added and incubated
   for another 5 min on platform rocker to quench the crosslinking
   reaction. Cells were washed and lysed in 2 mL cell lysis buffer A
   (20 mM Tris-HCl pH = 8.0, 85 mM KCl, and 0.5% NP-40) and incubated on
   ice for 10 min. Nuclei was pelleted by centrifugation at 1,350 g for
   5 min at 4°C. The nuclei was then resuspended in 750 μl lysis buffer B
   (50 mM Tris-HCl pH = 8.0, 10 mM EDTA, 1% SDS, plus protease inhibitor
   cocktail) and sonicated by using the Covaris S2 Focused-ultrasonicator
   until majority of DNA fragments were between 200 and 500 base pairs in
   size. The sonicated materials were then centrifuged at 20,000 g for
   10 min at 4°C to collect supernatant. 10% of the supernatant (75 μL)
   was used as input and 300 μL supernatant was used for each
   immunoprecipitation (IP) reaction.

   The 300 μL supernatant sample was diluted 5-fold by adding 1.2 ml IP
   dilution buffer (1.25% Triton X-100, 187.5 mM NaCl, 20 mM Tris-HCl pH =
   8.0, plus protease inhibitor cocktail), and incubated overnight at 4°C
   by rotating with the 30 μL protein G Dynabeads (Life Technologies)
   pre-incubated with H3K4me3 antibody (Active Motif, 39016). The beads
   were washed consecutively with 1 mL Low-salt wash buffer (0.1% SDS, 1%
   Triton X-100, 2 mM EDTA, 20 mM Tris-HCl pH 8.0, and 150 mM NaCl,
   twice), High-salt wash buffer (0.1% SDS, 1% Triton X-100, 2 mM EDTA,
   20 mM Tris-HCl pH 8.0, 500 mM NaCl, once), LiCl wash buffer (0.25 M
   LiCl, 1% NP-40, 1% Sodium Deoxycholate, 1 mM EDTA, 10 mM Tris-HCl pH
   8.0, once) and TE wash buffer (50 mM NaCl, 10 mM Tris pH 8.0, 1 mM
   EDTA, once) and incubated with 125 μL Elution Buffer (1% SDS/0.1 M
   sodium bicarbonate) for 15min on thermomixer at 1000 RPM and 65°C.
   Supernatant was collected by magnet separation from the beads. 5 μL 5M
   NaCl was added to each elute and incubated at 65°C overnight. 30 μL of
   input samples were incubated with 95 μL Elution Buffer and 5 μl 5M NaCl
   was used for reverse crosslinking. 2 μl of RNase A (0.5 mg/mL) was
   added to each IP and input sample for 30 min incubation at 37°C. 2 μL
   of Proteinase K (20 mg/mL) was then added to each sample and incubated
   for 2 h at 55°C. PCR Purification Kit (Qiagen) was used to recover DNA
   from each sample in 40 μL EB buffer.

   Traces of eluted DNA were used to library preparation using Illumina
   TruSeq Nano DNA LT Library Prep Kit (Cat# FC-121-4001), including
   end-repair, dA-tailing, indexed adaptor ligation and amplification.
   Each resulting indexed library were quantified and its quality accessed
   by Qubit and Agilent Bioanalyzer, and multiple libraries were pooled in
   equal molarity. The pooled libraries were then denatured, and
   neutralized, before loading onto NovaSeq 6000 sequencer at 300pM final
   concentration for 100b paired-end sequencing (Illumina, Inc.).
   Approximately 15-20M reads per library was generated. A Phred quality
   score (Q score) was used to measure the quality of sequencing. More
   than 90% of the sequencing reads reached Q30 (99.9% base call
   accuracy).

RNA-seq and ChIP-seq analysis and pathway enrichment analysis

   All RNA-seq and ChIP-seq datasets have been deposited in the Gene
   Expression Ominbus (GEO) with the accession ID ([201]GSE206112).

RNA-seq

   The reads were mapped to the human genome hg38 using STAR
   (v2.7.2a).[202]^39 RNA-seq aligner with the following parameter:
   “--outSAMmapqUnique 60”. Uniquely mapped sequencing reads were assigned
   to Gencode 31 gene using featureCounts (v1.6.2)[203]^40 with the
   following parameters: "-s 2 –p –Q 10 -O”. The data was filtered using
   read count >10 in at least 3 of the samples, normalized using TMM
   (trimmed mean of M values) method and subjected to differential
   expression analysis using edgeR (v3.36.0).[204]^41^,[205]^42 Gene
   ontology and pathway functional analysis was performed on differential
   expression gene with false discovery rate cut-off of 0.05 and absolute
   value of log2 of fold change cut-off of 0.25 using
   DAVID.[206]^43^,[207]^44 Gene set enrichment analysis was conducted by
   using hypergeometric test against human gene ontology and MsigDB v.6
   canonical pathways, with p < 0.01 as the significant cutoff.[208]^45

ChIP-seq

   Bowtie2[209]^46 was used for ChIP-Seq reads alignment on the human
   genome (hg38). Duplicated reads were removed using Picard [ref. 1].
   Peak calling of mapped ChIP-Seq reads were performed by MACS2[210]^47
   compared with input ChIP-Seq with a bonferroni adjusted cutoff of p
   value less than 0.01. Peaks called from multiple samples were merged.
   Merged peaks overlapping with ENCODE blacklist
   regions[211]^48^,[212]^49 were removed to form a final set of regions.
   Reads overlapping with these regions in different samples were counted
   by featureCounts.[213]^40 The data was filtered using at least 10 read
   counts in more than one of the samples, normalized using TMM (trimmed
   mean of M values) method and subjected to differential analysis using
   edgeR (v3.36.0).[214]^41^,[215]^42 Gene ontology and pathway functional
   analysis was performed on genes whose upstream 2kbp having differential
   peak signals with false discovery rate cut-off of 0.05 and absolute
   value of log2 of fold change cut-off of 0.25 using DAVID.[216]^43

   Ref. 1: Broad Institute. (Accessed: 2018/02/21; version 2.17.8).
   “Picard Tools.” Broad Institute, GitHub repository.
   [217]http://broadinstitute.github.io/picard/.

Quantification and statistical analysis

   Each experiment was performed in replicates (biological and technical)
   to confirm observed phenotypes and data reproducibility. Data presented
   in figures was created in GraphPad Prism 9 and plotted as mean ± S.E.M.
   Statistical analysis was done in GraphPad Prism 9 using two-sided
   paired or unpaired t-tests. p values ≤0.05 were considered
   statistically significant.

Acknowledgments