Abstract

   Acquired drug tolerance has been a major challenge in cancer therapy.
   Recent evidence has revealed the existence of slow-cycling persister
   cells that survive drug treatments and give rise to multi-drug-tolerant
   mutants in cancer. Cells in this dynamic persister state can escape
   drug treatment by undergoing various epigenetic changes, which may
   result in a transient metabolic rewiring. In this study, with the use
   of untargeted metabolomics and phenotype microarrays, we characterize
   the metabolic profiles of melanoma persister cells mediated by
   treatment with vemurafenib, a BRAF inhibitor. Our findings demonstrate
   that metabolites associated with phospholipid synthesis, pyrimidine,
   and one-carbon metabolism and branched-chain amino acid metabolism are
   significantly altered in vemurafenib persister cells when compared to
   the bulk cancer population. Our data also show that vemurafenib
   persisters have higher lactic acid consumption rates than control
   cells, further validating the existence of a unique metabolic
   reprogramming in these drug-tolerant cells. Determining the metabolic
   mechanisms underlying persister cell survival and maintenance will
   facilitate the development of novel treatment strategies that target
   persisters and enhance cancer therapy.

   Keywords: cancer persisters, BRAF, melanoma, metabolomics, phenotype
   microarrays, drug-tolerance

1. Introduction

   Metastatic melanoma makes up roughly 1% of skin cancer cases in the
   U.S., and yet, it is responsible for more deaths per year than all
   other skin cancer types combined [[30]1]. According to data collected
   between 2014 and 2018 in the United States, the yearly incidence rate
   for melanoma was 22.8 per 100,000 [[31]2], with an estimated recurrence
   rate of 8.8% [[32]3]. Davies et al. reported rapidly accelerated
   fibrosarcoma B-type kinase (BRAF) mutations in 59% of melanomas from a
   library of cancer cell lines, with the V600E substitution being the
   most common [[33]4]. The mitogen-activated protein kinase/extracellular
   signal-regulated kinase (MAPK/ERK) signaling pathway is a kinase
   cascade pathway involved in cell proliferation, in which the BRAF
   protein activates mitogen-activated protein kinase kinase (MEK or
   MAPKK) [[34]5]. Therefore, a mutation in the BRAF protein can lead to
   uncontrolled cell proliferation and the spread of tumor cells. As the
   BRAF V600E mutation has been found in over 50% of malignant melanomas
   [[35]6], BRAF inhibitors, e.g., vemurafenib, are the most common form
   of therapeutics administered for melanoma treatment.

   It is well known that cancer cells have altered metabolic states;
   typical metabolic alterations include the Warburg effect (increased
   aerobic glycolysis activity) and increased use of glutamine to support
   both the tricarboxylic acid (TCA) cycle and lipid synthesis
   [[36]7,[37]8]. Melanoma cells have been shown to express
   hypoxia-inducible factor 1 alpha (HIF1α) at an abnormally high level
   under normoxia, which shifts the central carbon metabolism in favor of
   aerobic glycolysis [[38]9]. The pyruvate dehydrogenase (PDH) complex
   also plays an important role in both metabolic rewiring and
   tumorigenesis in melanoma. In melanomas with the BRAF V600E mutation,
   Kaplon et al. found that activation or inactivation of the PDH complex
   leads to oncogene-induced senescence or tumorigenesis, respectively
   [[39]10], highlighting the importance of the Warburg effect in melanoma
   progression. However, central carbon metabolism is not necessarily
   uniform in all melanoma cancers. Ho et al. studied the interactions of
   monocarboxylate transporters (MCTs) with the aerobic glycolysis and
   oxidative phosphorylation pathways [[40]11] and found that some
   melanoma cells (within a single tumor) are less dependent on aerobic
   glycolysis than others. They demonstrated that MCTs can facilitate the
   transfer of lactate from a cell subpopulation with high levels of
   aerobic glycolysis to cells that are more dependent on oxidative
   phosphorylation, creating a heterogeneous and collaborative tumor
   microenvironment [[41]11].

   Drug tolerance has also been observed as a heterogeneous trait in
   cancer cells [[42]12]. A subpopulation, known as persister cells, has
   been shown to adopt a transient drug-tolerant state in cancer cell
   populations [[43]12]. These persisters cells, which are described as
   slow-cycling cells [[44]13], can act as a reservoir for the emergence
   of multi-drug-resistant mutants and contribute to cancer relapse
   [[45]14]. Recent evidence shows that persisters have unique metabolic
   profiles compared to the bulk cancer population [[46]15,[47]16]. A
   study conducted by Hangeur et al. showed that drug-tolerant persister
   cells are selectively vulnerable to the lipid hyperoxidase (GPX4)
   inhibitor and require the enzyme to survive ferroptosis [[48]15]. In
   addition, studies have demonstrated that BRAF-inhibitor-tolerant cells
   shift their metabolic activity away from aerobic glycolysis and toward
   oxidative phosphorylation, which is mediated via fatty acid oxidation
   [[49]16]. In our previous study, we explored the impacts of
   conventional chemotherapeutics (cytotoxic medications) on persister
   metabolism and found that chemotherapeutics induce a transient shift
   from aerobic glycolysis to oxidative phosphorylation [[50]17]. When it
   comes to targeted therapeutics, melanoma persister cells are generally
   derived by co-treatment with BRAF/MEK inhibitors [[51]16], making it
   unclear how persister metabolism is affected by each drug,
   individually. In this study, with the use of untargeted metabolomics,
   high-throughput assays (phenotype microarrays), and enzymatic
   measurements of glucose and lactate levels, we explored
   BRAF-inhibitor-induced persister metabolism. Our integrated approach
   allowed us to identify energy sources/substrates that are selectively
   preferred by vemurafenib persisters.

2. Results

2.1. Vemurafenib Persister Cells Are Slow-Cycling Cells That Are Reversibly
Drug Tolerant

   Drug-tolerant persister cells were generated by treating A375 cells
   with vemurafenib (VEM) ([52]Figure 1a). VEM, which is commonly used in
   targeted therapy for melanoma with the BRAF V600E-positive mutation, is
   a competitive inhibitor of the mutated BRAF protein [[53]18]. We first
   treated A375 cells with different concentrations of VEM for 3 days to
   generate a kill curve (survival ratio vs. VEM concentration)
   ([54]Figure 1a). The data show that the half maximal inhibitory
   concentration (IC[50]) of VEM for A375 cells was ~100 nM and a
   treatment concentration higher than 10 × IC[50] did not significantly
   affect the persister ratio (i.e., cell survival ratio) [[55]17]. As
   persisters survive high concentrations of drugs, persister cells were
   isolated by treating A375 cells with VEM at 100 × IC[50] concentration
   for 3 days, consistent with previous studies [[56]17,[57]19,[58]20].
   After treatment, the cells were cultured in a fresh, drug-free growth
   medium for 24 h to remove dead/apoptotic cells. A cell viability
   imaging assay and fluorescence microscopy were used to validate that
   the isolated persisters were viable cells ([59]Figure S1a).
   Furthermore, an annexin-V apoptosis assay was used to quantify the
   apoptotic cells in our samples [[60]21]. During the early stages of
   apoptosis, phosphatidylserine (PS) is exposed to the outer leaflets of
   the cell membrane, which has high specificity toward annexin-V in the
   presence of calcium [[61]22]. Our analysis showed that the isolated
   persister cells are not apoptotic ([62]Figure 1b). Since persister
   cells are reversibly tolerant to treatments, we re-cultured these cells
   in a fresh medium and treated the daughter cells (i.e., progenies) with
   VEM ([63]Figure 1a). As expected, the progenies of the persister cells
   were sensitive to VEM treatment. We also conducted clonogenic survival
   assays (CSAs) to assess the persister cells’ colonization capability
   and used live/dead cell fluorescent probes and flow cytometry to
   quantify persister cells after the removal of the drug. The data show
   that persister and colony counts were not significantly different
   ([64]Figure 1c), verifying that persister cells largely colonized upon
   removal of VEM.

Figure 1.

   [65]Figure 1
   [66]Open in a new tab

   Persisters are slow-cycling, drug-tolerant cells. (a) A375 cells were
   treated with VEM at indicated concentrations for 3 days. After
   treatment, surviving cells were collected for the assessment of their
   viability with trypan blue staining. The survival fraction was
   calculated by normalizing the number of live cells in the treatment
   culture with the total number of cells in the untreated control group.
   Number of biological replicates n = 4. (b) A375 cells after VEM
   treatment were collected and cultured in a fresh, drug-free growth
   medium for 24 h. Then, the cells were stained with an
   annexin-V/fluorescein isothiocyanate (FITC) conjugate and propidium
   iodide (PI) to detect apoptotic cells. Of note, PI is a
   membrane-impermeant dye that can only penetrate the damaged, permeable
   membranes of dead cells. The cell populations were gated to represent
   (I) live (FITC^−/PI^−), (II) early apoptotic (FITC^+/PI^−), (III) late
   apoptotic (FITC^+/PI^+), and (IV) dead (FITC^−/PI^+) cells. (c) After
   treatment, A375 cells were collected to test their viability with
   STYO60/SYTOX green staining and clonogenic survival assays (CSA) (see
   [67]Section 4). ns: not significant (t-test, p < 0.05). n = 4. (d) A375
   cells pre-stained with CFSE were either treated with VEM or left
   untreated. At indicated time points, the fluorescence of the cells was
   measured with flow cytometry. n = 4.

   As persister cells are described as slow-cycling cells, we performed
   cell proliferation analysis with carboxyfluorescein succinimidyl ester
   (CFSE), a fluorescent dye that can readily diffuse through cell
   membranes and produce a stable fluorescent signal [[68]23]. The cells
   were stained with the dye and cultured for 3 days either in the
   presence or in the absence of VEM. The cell proliferation was assessed
   for treated and untreated groups by monitoring the dilution of the
   fluorescent signal with flow cytometry. As expected, our flow cytometry
   analysis showed that VEM-treated cultures had retained a higher signal
   of fluorescence compared to the untreated control group ([69]Figure
   1d). Furthermore, we imaged CFSE-loaded cells before and after
   treatment with fluorescence microscopy ([70]Figure S1b) and found that
   the VEM-treated cells had undergone morphological changes and retained
   higher green fluorescence compared to the untreated control group. This
   observation further supports the notion that persister cells are
   slow-proliferating cells, potentially induced by VEM treatment.
   Finally, to assess the impact of the treatment period, cells were
   treated with VEM (100 × IC[50]) for 9 days and the surviving cells were
   assessed using the aforementioned assays, showing that the effects of
   9-day treatment on cell viability, morphology, and growth are very
   similar to those obtained from 3-day treatment ([71]Figure S1a–c).

2.2. VEM Treatment Affects the Expression Levels of Cancer Stem Cell
Biomarkers

   As cancer stem cells (CSCs) are often associated with dormancy, slow
   growth, and drug tolerance, we measured the common melanoma CSCs
   biomarkers (CD271, CD44, CD34, and aldehyde dehydrogenase activity)
   ([72]Figure 2) to determine if the isolated persisters are CSCs
   [[73]24]. There was no significant difference in CD34 and CD44
   expression between persister and untreated control cells ([74]Figure
   2c,d). However, the expression level of CD271 gradually increased in
   VEM-treated cells when compared to untreated cells ([75]Figure 2b).
   This observation has previously been reported by Rambow et al., where
   they showed that, upon BRAF inhibition, melanoma cells demonstrate a
   high expression of nerve growth factor receptor (NGFR or CD271)
   [[76]25]. Additionally, it has been shown that a transient
   overexpression of CD271 can result in a phenotypic switch to a low
   proliferative and highly invasive state in cells while increasing the
   tolerance of the cells to BRAF inhibitors [[77]26]. With the ALDEFLUOR
   assay, we measured the activity of aldehyde dehydrogenase (ALDH), a
   functional biomarker of melanoma stem cells, in both persisters and
   untreated control groups. Contrary to our expectation, VEM-treated
   cells showed lower ALDH activity compared to untreated control cells
   ([78]Figure 2a). As CSCs have higher levels of stem cell markers than
   the bulk population, our observations indicate that VEM persisters are
   not necessarily pre-existing cancer stem cells and drug treatment can
   up- or down-regulate the expression levels of CSC biomarkers in the
   cells.

Figure 2.

   [79]Figure 2
   [80]Open in a new tab

   Expression of CSC markers in persister cells. (a) A375 cells were
   treated with VEM or left untreated for 3 days. At indicated time
   points, the ALDH activity of the cells (red) was assessed with the
   ALDEFLUOR assay. Cells treated with ALDH inhibitor 4-(dimethylamino)
   benzaldehyde (DAEB), highlighted in blue, were used as a negative
   control. (b–d) Expressions of CSC biomarkers (CD271, CD44, and CD34)
   were measured with their respective phycoerythrin (PE)-conjugated
   antibodies. Cells treated with their isotype controls were used to
   determine CSC-negative (−) and CSC-positive (+) cells. Live/dead
   staining was used to gate the live cells.

2.3. VEM-Induced Persister Cells Exhibit an Altered Metabolic Profile

   Metabolic rewiring is a common hallmark of cancer persister cells.
   Persisters undergo such alterations to meet their energy requirements
   and enable their survival in the presence of therapeutics. These
   metabolic alterations can be unique or conserved in various persister
   phenotypes [[81]12,[82]15,[83]16]. After confirming that VEM persisters
   are live, reversibly drug-tolerant cells that are different from CSCs
   ([84]Figure 1 and [85]Figure 2), we conducted untargeted metabolomics
   to study and identify persister-specific metabolic alterations. For the
   metabolomics study, persister cells were generated by treating the
   cells with VEM (100 × IC[50]) for 3 days. The metabolomics library
   consisted of 689 metabolites from the following super pathways: amino
   acids, peptides, carbohydrates, energy, lipids, nucleotides,
   cofactors/vitamin, and xenobiotics. The metabolomics data were
   normalized based on the total protein concentration, and statistical
   analysis was conducted with an ANOVA test (p < 0.05). We also performed
   pathway enrichment analysis with MetaboAnalyst for subsets of
   metabolites that were either upregulated or downregulated in persister
   cells ([86]Figure 3c,d) [[87]27]. Our data show that the concentrations
   of 469 metabolites were significantly altered in persister cells when
   compared to the untreated control group ([88]Figure 3 and [89]Tables S1
   and S2). Furthermore, ~67.6% (317) of the identified metabolites were
   significantly upregulated while ~32.4% (152) were downregulated in
   persister cells compared to the untreated control ([90]Table S2).

Figure 3.

   [91]Figure 3
   [92]Open in a new tab

   Metabolic profiles of VEM-induced persister cells. (a) VEM-treated and
   untreated A375 cells were collected for mass spectrometry analysis to
   measure their metabolite contents. The data generated with metabolomics
   were clustered (unsupervised) using the Clustergram function in MATLAB.
   Each column represents a biological replicate; each row represents a
   metabolite. n = 4. (b) A simplified metabolic network of persister
   cells (created with Biorender). Red and blue represent upregulated and
   downregulated metabolites in persisters when compared to the control
   group, respectively (ANOVA, p < 0.05). (c,d) Pathway enrichment
   analysis for all upregulated and downregulated metabolites with
   MetaboAnalyst, respectively.

   Of the 317 upregulated metabolites, 161 were involved in the lipid
   super pathway. The enrichment analysis further validated that a
   majority of the metabolites that were upregulated in persister cells
   were involved in lipid biosynthesis ([93]Figure 3b,c).
   Phosphatidylcholine (PC), phosphatidylethanolamide (PE),
   monoacylglycerol, lysophospholipid, and sphingomyelins were primarily
   upregulated, while metabolites involved in fatty acid metabolism were
   downregulated in persister cells ([94]Figure 3a–d and [95]Table S2). In
   addition to lipids, metabolites associated with lysine,
   purine/pyrimidine, thiamine, and lactose metabolism were upregulated,
   while one-carbon (betaine, glycine, and serine) metabolism,
   branched-chain amino acid (BCAA) metabolism, and glutamate metabolism
   were downregulated in persisters compared to control cells ([96]Figure
   3a–d, and [97]Table S2). Our data also show an alteration of
   carbohydrate metabolism; particularly, glucose and glucose 6-phosphate
   were significantly upregulated in persister cells. Interestingly,
   although we did not observe significant alterations in metabolic
   intermediates of glycolysis and tricarboxylic acid (TCA) cycle, two TCA
   cycle substrates, alpha-ketoglutarate and succinate, were downregulated
   in persister cells ([98]Figure 3b). The observed effect can be
   attributed to the overall alteration of amino acid metabolism as
   alpha-ketoglutarate and succinate are involved in various pathways,
   including BCAA, gamma-aminobutyric acid (GABA) shunt, and glutamate
   metabolism ([99]Figure 3b). Overall, while our metabolomics data
   identified specific metabolites that are significantly altered in
   persisters, it is not clear which substrates/carbon sources persister
   cells efficiently use to maintain the biosynthesis of these detected
   molecules. Therefore, additional experiments (see below) are needed to
   further characterize persister cell metabolism.

2.4. TCA Cycle Activity of Persister Cells Is Not Significantly Different
from That of Control Cells

   We used phenotype microarrays (Biolog Inc., Hayward, CA, USA) to
   determine the metabolites that are efficiently used by persister cells.
   Mitoplate arrays, which mainly include TCA cycle substrates, were used
   to assess the rates of oxidative phosphorylation of VEM-treated and
   untreated control cells. This assay employs a tetrazolium dye that
   produces water-soluble formazan crystals when reduced by mitochondrial
   reductases. The rate of metabolism of specific metabolites is measured
   by monitoring the color change associated with formazan production
   (optical density at 590 nm (OD[590])) with a plate reader. In addition,
   the cells are permeabilized with saponin so that the tetrazolium dye
   can be intracellularly reduced by mitochondria.

   In our previous study, we showed that the levels of TCA metabolites are
   downregulated in drug-tolerant cells (obtained from chemotherapeutic
   treatments) because of the increased consumption rates of these
   intermediates by the cells [[100]17]. From the mitoplate assays, we
   observed a slight increase in the consumption of succinate in VEM
   persister cells ([101]Figure S2). This observation corroborates our
   metabolomics data, which showed an overall downregulation of succinate
   molecules in VEM persisters compared to the untreated control. However,
   no significant difference was observed in the consumption rates of
   other TCA cycle metabolites ([102]Figure S2). Although drug-tolerant
   cells are generally shown to be less dependent on aerobic glycolysis
   (the Warburg effect) and more reliant on oxidative phosphorylation
   [[103]16,[104]28,[105]29], our metabolomics and mitoplate data do not
   show this trend in VEM persisters.

2.5. Lactic Acid Consumption Is Significantly Upregulated in VEM Persister
Cells

   A phenotype microarray (PM-M1) (Biolog Inc.) containing 91 carbon and
   nitrogen substrates was used to identify metabolites that are
   efficiently catabolized by persisters. Similar to the mitoplate assay,
   cellular metabolic activities are measured by a tetrazolium dye in the
   PM-M1 assay. However, unlike the mitoplate assay, cells are not
   permeabilized in the PM-M1 assay, in which the cells are cultured for 2
   days in a minimal medium supplemented with fetal bovine serum (FBS),
   glutamine, and the substrate of interest (see [106]Section 4).

   After transferring VEM-treated and untreated control cells to PM-M1
   arrays, metabolic activities of the cells were measured at t = 0 h, 24
   h, and 48 h with the tetrazolium dye. We observed that carbon sources
   such as D-turanose, D-mannose, glycogen, and D-maltose were consumed
   less by persisters when compared to control cells ([107]Figures S3–S5).
   We also observed significant differences in glucose, lactic acid,
   inosine, and adenosine metabolism between persisters and untreated
   cells ([108]Figure 4 and [109]Figures S3–S5). Interestingly, although
   untreated cells seemed to have higher consumption rates of glucose at t
   = 0 h and 24 h, the glucose consumption rates were found to be low in
   persister cells at initial time points ([110]Figure 4). Increased
   intracellular concentrations of glucose and glucose 6-phosphate in
   persister cells determined by metabolomics analysis ([111]Figure 3b)
   may be due to the decreased consumption rates of these metabolites by
   the persister cells ([112]Figure 4). However, lactate metabolism is
   significantly upregulated in persister cells ([113]Figure 4), while the
   metabolism of inosine and adenosine is more active in control cells
   ([114]Figure 4 and [115]Figures S3–S5). Lactic acid is a byproduct of
   glycolysis and glutaminolysis, and increased levels of lactate
   production in cancer cells have been extensively studied and linked
   with increased aerobic glycolysis. However, the observed difference in
   lactic acid use ([116]Figure 4) may be due to the conversion of lactic
   acid to pyruvate and acetyl-coA, which serve as metabolic intermediates
   for lipid and amino acid metabolism in persister cells ([117]Figure
   3b). Lastly, both adenosine and inosine are nucleosides that have been
   linked to cell proliferation and cell death in cancer cells [[118]30]
   and both metabolites are preferred by untreated control cells
   ([119]Figure 4). This observation is in alignment with our metabolomics
   data, as we see an accumulation of inosine- and adenosine-containing
   metabolites in persister cells, potentially due to their reduced
   consumption rates in the cells.

Figure 4.

   [120]Figure 4
   [121]Open in a new tab

   Assessing the consumption rates of various substrates in persister
   cells. Phenotype microarrays were used to measure the consumption rates
   of various substrates in VEM persister and control groups at (a) 0 h,
   (b) 24 h, and (c) 48 h. Consumption rates were measured with a
   tetrazolium-based dye at 590 nm (OD[590]). The absorbance was
   normalized by using t = 0 h and glutamine control data (see
   [122]Section 4). Data points and error bars represent the mean and the
   standard error, respectively. Statistical analysis was performed using
   a linear regression analysis (F-Statistics, *** p < 0.001). n = 4.

2.6. Persister Cells Have Increased Viability in a Minimal Medium

   To further validate the phenotype microarray data, we measured glucose
   and lactic acid concentrations in the cultures in which VEM-treated and
   untreated control cells were cultured in the presence of glucose or
   lactic acid under PM-M1 assay conditions. Our results show that while
   glucose consumption at t = 24 h was significantly higher in untreated
   control cells compared to VEM persisters, the glucose consumption of
   persister cells increased to a level similar to the untreated control
   by 48 h ([123]Figure 5a), consistent with our PM-M1 results
   ([124]Figure 4). Both glucose consumption and phenotype microarray data
   verify the existence of a longer lag phase in persister cells. We also
   measured the number of viable cells (although confluent cell cultures
   were used for PM-M1 assays as described in [125]Section 4) and showed
   that the number of cells was slightly higher in the control group in
   the presence of glucose; however, the difference between persister and
   control groups was not statistically significant ([126]Figure 5b). Our
   measurement of lactic acid in untreated control samples showed minimal
   or no changes in lactic acid concentration; therefore, we were not able
   to calculate the lactic acid consumption by control cells. However, VEM
   persister cells were able to consume lactic acid ([127]Figure 5c), as
   predicted by PM-M1 data ([128]Figure 4). Interestingly, cell count data
   showed that, at 48 h, the survival ratio of untreated control cells was
   significantly lower compared to that of VEM persister cells in a
   minimal medium containing lactic acid ([129]Figure 5d).

Figure 5.

   [130]Figure 5
   [131]Open in a new tab

   Measurement of glucose and lactic acid consumption. After treatment
   with VEM, cells were cultured in a minimal medium consisting either
   glucose or lactic acid. (a–d) The substrate consumption rates and live
   cell numbers were measured for cultures consisting of glucose (a,b) or
   lactic acid (c,d) at indicated time points. n = 4. (e) Untreated or
   VEM-treated cells were cultured in various conditions to assess their
   viability. n = 4. Data points and error bars represent the mean and the
   standard error, respectively. Statistical comparison was conducted with
   a pairwise t-test (* p < 0.5, ** p < 0.01, and *** p < 0.001).

   To comprehensively study the effects glucose and lactic acid on cell
   viability, we cultured the untreated or VEM-treated cells for 48 h in
   the minimal medium consisting of FBS and glutamine and supplemented
   with either lactic acid, glucose, or both substrates. Then, at 48 h,
   the cells were stained with live/dead probes and analyzed with a flow
   cytometer to enumerate live cells. The survival fraction was then
   calculated by normalizing the cell counts with the initial number of
   cells ([132]Figure 5e). As expected, the viability of both control and
   persister cells was found to be higher when the medium had glucose.
   However, the viability of the untreated control group dropped
   significantly in the absence of glucose and the presence of lactic acid
   in the minimal medium that lacked glucose did not improve the viability
   of control cells ([133]Figure 5e). On the contrary, the viability of
   VEM persisters was not affected by lactic acid and persister cells can
   still survive in a minimal medium supplemented with FBS and glutamine
   without glucose and lactic acid ([134]Figure 5e). These observations
   further highlight the significance of metabolic reprogramming for
   persister cell survival.

3. Discussion

   The emergence of drug-tolerant persister cells has become one of the
   major challenges in cancer treatment. The ability of persister cells to
   avoid conventional therapeutics can lead to a high relapse rate and
   poses a significant challenge in the complete eradication of tumor
   cells. With this study, we aimed to characterize the metabolic profiles
   of persisters that are tolerant to vemurafenib, a BRAF inhibitor.
   Identifying the metabolic pathways of tolerant cells can offer
   potential therapeutic targets, which has been an overarching goal of
   many recent studies. Methods employing various transcriptomics
   techniques (RNA-seq, single-cell RNA-seq, DNA microarrays) have been
   used to explore the metabolic alterations in persister cells
   [[135]12,[136]15,[137]16]. Our study employed untargeted metabolomics,
   which can provide a global/comprehensive analysis of the persister
   metabolome. Although recent studies have explored the advantages of
   metabolic flux analysis with isotope-labeled metabolites, this does not
   provide a broad overview of the persister metabolome.

   Although untargeted metabolomics is a powerful tool [[138]31],
   discerning whether the identified metabolites are consumed by the cells
   or are the products of certain pathways is quite challenging. To
   address this issue, we employed phenotype microarray assays that
   measure the utilization rates of various substrates via a tetrazolium
   dye. The key underlying mechanism of this assay is that the utilization
   rate of a substrate correlates with the rate of dye reduction; thus,
   these assays in combination with metabolomics can allow us to infer
   whether a given biochemical source is being catabolized. In addition,
   we employed a modified version of the microarray assay, namely the
   mitoplate assay, which measures the consumption rates of substrates
   associated with the TCA cycle. The modified version of the tetrazolium
   dye is expected to be reduced by electrons primarily released from
   cytochromes. This technique can indeed be used to infer the rate of
   oxidative phosphorylation in the sample being tested. The most popular
   method for assessing oxidative phosphorylation is the seahorse assay,
   which measures the oxygen consumption rate (OCR) as well as the
   glycolytic flux [[139]32]. However, the seahorse assay does not provide
   insights into the utilization rates of substrates contributing to the
   increased OCR.

   Our metabolic analysis showed that almost half of the upregulated
   metabolites in persister cells are associated with lipid metabolism.
   Our subsequent assays indicated that carbon sources, such as lactate,
   are potentially diverted to anabolic pathways associated with lipid and
   amino acid metabolism in persisters. Lactate is used for many cellular
   processes involved in metastasis, angiogenesis, and, more importantly,
   immunosuppression of cancer [[140]33]. Furthermore, lactic acid can be
   reversibly converted to pyruvate and acetyl-coA, which may act as an
   energy source for fatty acid oxidation [[141]34] or serve as metabolic
   intermediates for certain amino acid and lipid metabolism ([142]Figure
   3b).

   The alteration of lipid metabolism in drug-tolerant cells has been
   shown by prior studies [[143]35]. PC, PE, lysophospholipid, and
   sphingomyelins are major components of cell membranes and play
   significant roles in cell proliferation, apoptosis, and cell migration
   [[144]36]. Phospholipids and sphingolipids are also closely associated
   with drug resistance and tumor progression in multiple cancers,
   including melanoma [[145]37]. Delgado-Goni et al. demonstrated that
   limiting the exogenous lipid content results in an overall increase in
   VEM sensitivity for resistant BRAF-mutated melanoma cells [[146]38]. De
   novo fatty acids are continually used by cancer cells to synthesize
   lipids required for membrane production and to provide energy through
   β-oxidation [[147]39].

   Nucleotide metabolism (pyrimidine and purine) represents another class
   of metabolites that was altered in persister cells. With microarray
   experiments, we observed that persister cells had lower consumption
   rates for adenosine and inosine compared to untreated cells. This
   difference was noticeably greater in the inosine consumption rate.
   Inosine can be produced by the catabolism of adenosine. Soares et al.
   have shown that adenosine causes cell proliferation by activating the
   adenosine receptor (AR), while inosine enhances proliferation by
   activating the receptor A[3]AR [[148]40]. One-carbon metabolism, which
   was shown to be downregulated in persister cells, can be used for the
   biosynthesis of nucleotides [[149]41]. Along with the pentose phosphate
   pathway (PPP), one-carbon metabolism is involved in NADPH production
   and the maintenance of redox and methylation states is required for
   cell proliferation [[150]42]. Lastly, in amino acid metabolism,
   metabolites involved in BCAA were significantly altered in persister
   cells. BCAA metabolism in cancer has been extensively studied as it is
   required for many cellular processes, including protein synthesis and
   energy production [[151]43,[152]44]. Branched-chain aminotransferase
   1/2 (BCAT1/ BCAT1) enzymes, which are involved in BCAA degradation, are
   proposed to be a prognostic marker for cancer [[153]45]. A study by
   Wang et al. also demonstrated that epigenetic upregulation of BCAT1 can
   promote tolerance to tyrosine kinase inhibitor in lung cancer cells
   [[154]20].

   Along with lipid metabolism, we expected that persister cells would
   have a significant difference in energy metabolism, primarily in the
   TCA cycle and oxidative phosphorylation. Studies have shown that
   persister cells generally exhibit an increased rate of oxidative
   phosphorylation compared to bulk tumor populations [[155]16,[156]28].
   However, in this study, we did not see a significant difference in the
   consumption rates of TCA substrates except for succinate. This can be a
   result of differences in experimental details between studies. For
   instance, we generated persister cells with a single drug treatment
   while the majority of the studies have used combinations of BRAF/MEK
   inhibitors and/or chemotherapeutics. A study conducted by Parmenter et
   al. showed similar outcomes where a single treatment with a BRAF
   inhibitor resulted in a decrease in the OCR of melanoma cells
   [[157]46], although they speculated that long-term treatments may
   eventually shift persister metabolism toward oxidative phosphorylation.

   In this study, we showed that VEM persisters can use lactate more
   efficiently than untreated control cells. Although investigating the
   molecular mechanism underlying this observed phenomenon is beyond the
   scope of this study, we hypothesize that targeted therapeutics (e.g.,
   the BRAF inhibitor, VEM) induce cell dormancy by directly inhibiting
   cell-proliferation signaling pathways. Oncogenic mutations in RAS genes
   (KRAS, NRAS, and HRAS) or RAF genes (RAF-1, BRAF, and A-RAF) occur in
   many cancer types, including the melanoma cells [[158]47]. BRAF is a
   serine/threonine-protein kinase and acts upstream in several signaling
   pathways (e.g., MEK/ERK and PI3K/AKT) that promote aerobic glycolysis
   and enhance the expression of enzymes involved in anabolic pathways
   (e.g., protein and lipid synthesis) by activating various transcription
   factors, such as HIF1/2, MYC, FoxO, and STAT3 [[159]47,[160]48]. These
   transcription factors are known to induce glucose transporters and
   glycolytic and anabolic enzymes
   [[161]49,[162]50,[163]51,[164]52,[165]53]. Studies show that the
   metabolism of drug-tolerant melanoma cells may be associated with
   increased mitochondrial oxidative phosphorylation and decreased
   glycolysis and lactate synthesis [[166]54,[167]55,[168]56,[169]57],
   which may indeed increase lactate consumption in the cells. Lactate
   consumption can interrupt cellular energy homeostasis by deactivating
   AMP-activated protein kinase (AMPK), resulting in the overexpression of
   regulatory element-binding protein 1 (SREBP1), stearoyl-CoA, and
   desaturase-1 [[170]58]. Upregulation of these enzymes protects cells
   against ferroptosis by increasing the production of exogenous
   monounsaturated fatty acids [[171]58].

   The existence of persisters is a major obstacle in cancer therapy.
   Eradication of these drug-tolerant cells is a monumental challenge
   because the mechanisms underlying their formation and survival are
   highly complex and diverse. The therapeutic promise of targeting a
   metabolic mechanism in persister cells garners noteworthy attention in
   the field, as metabolism represents a rich source of targets for
   anti-persister strategies [[172]15,[173]16]. Although we focused on
   melanoma cells, the suggested methodologies integrating untargeted
   metabolomics and phenotype microarrays can be readily extrapolated to
   other cell lines, enabling the assessment of the physiological
   capabilities of a wide variety of persisters.

4. Materials and Methods

4.1. Cell Culture Conditions

   The melanoma A375 cell line was purchased from American Type Culture
   Collection (ATCC) (Manassas, VA, USA). If not otherwise specified, all
   materials were obtained from Thermo Fisher Scientific (Waltham, MA,
   USA). Melanoma cells were cultured in Dulbecco’s modified Eagle’s
   medium (DMEM) supplemented with 10% fetal bovine serum (FBS), 100 units
   of penicillin, and 100 µg streptomycin/mL. Cells were cultured in a
   humidified incubator at 37 °C and 5% CO[2]. Phenotype microarray plates
   and assay solutions were purchased from Biolog, Inc. (Hayward, CA,
   USA). PE-conjugated antibodies (CD271 (catalog# 557196), CD44 (catalog#
   555479), or CD34 (555822)) and their IgG isotype controls were obtained
   from BD science (San Jose, CA, USA). The ALDEFLUOR assay kit was
   obtained from STEMCELL Technologies (Cambridge, MA, USA). The BRAF
   inhibitor, vemurafenib (VEM), was dissolved in dimethylsulfoxide (DMSO)
   to prepare stock solutions.

4.2. Generating Persister Kill Curves

   To generate biphasic kill curves, 3 × 10^5 cells were seeded in each
   well of a 6-well plate. The cells were maintained in 3 mL of DMEM for
   24 h in a humidified incubator at 37 °C and 5% CO[2]. After 24 h, the
   medium was removed and replaced with a fresh medium with varying
   concentrations of VEM. After the cells were treated with VEM for 3
   days, the surviving cells were washed with 3 mL of Dulbecco’s
   phosphate-buffered saline (DPBS) two times. The cells were detached
   with 300 µL of trypsin-EDTA (0.25% trypsin and 0.9 mM EDTA) and then
   collected in 1.5 mL microcentrifuge tubes after adding 1 mL of DMEM,
   which deactivates the trypsin. The cell suspension was centrifuged at
   900 revolutions per minute (rpm) for 5 min, and the supernatant was
   removed. The cell pellet was then re-suspended in fresh DMEM, and live
   cells were quantified with trypan blue staining [[174]59] using an
   automated cell counter (catalog# A27977, Thermo Fisher Scientific,
   Waltham, MA, USA). The survival ratio was calculated by normalizing the
   cell count with the total number of cells in the untreated control
   group. Finally, the survival ratios and drug concentrations were
   plotted to generate the kill curves.

4.3. Isolating Persister Cells

   Approximately 2.5 × 10^6 cells were transferred to 15 mL of DMEM in a
   T-75 flask. The cells were cultured for 24 h in a humidified incubator
   maintained at 37 °C and 5% CO[2]. After 24 h, the medium was replaced
   with a fresh medium containing 10 μM VEM. After the cells were treated
   with VEM for 3 days, they were washed with 10 mL of DPBS two times and
   detached from the flasks with 2 mL of trypsin-EDTA. Then, 5 mL of DMEM
   was added to deactivate the trypsin and the cells were centrifuged at
   900 rpm for 5 min. The supernatant was removed, and the cells were
   resuspended in fresh DMEM and transferred to a T-75 flask. The cells
   were further incubated at 37 °C in the presence of 5% CO[2] for 24 h to
   remove dying/dead cells as they cannot adhere to the flask surface.
   Following the incubation, the supernatant with dead cells was discarded
   and the live cells were detached and collected for the experiments
   described below. The control group (untreated cells) underwent the same
   procedure, receiving the solvent-only (DMSO) treatment.

4.4. Assessing the Cell Viability with Microscopy

   The viability of cells after VEM treatment was assessed with the
   ReadyProbes Cell Viability Imaging kit (Blue/Green) (catalog#
   [175]R37609, Thermo Fisher Scientific) as described by the vendor’s
   protocol. The viability imaging kit consists of cell-permeant NucBlue
   and cell-impermeant NucGreen dyes for visualizing live (blue) and dead
   (blue + green) cells. DAPI (excitation: 360 nm; emission: 460 nm) and
   GFP (excitation: 470 nm; emission: 525 nm) channels from EVOS M7000
   fluorescence microscopy (catalog# AMF7000, Thermo Fisher Scientific)
   were used to measure the fluorescence signals. Untreated and dead cells
   were used as negative and positive controls, respectively. Cells were
   treated with 70% ethanol for 30 min to generate dead cells.

4.5. Apoptosis Assay

   The annexin-V FITC/PI kit (catalog# P50-929-7, Thermo Fisher
   Scientific) was used to detect apoptotic cells in VEM-treated and
   untreated cultures, as described in our previous study [[176]17].
   Briefly, cells surviving the treatment were collected and centrifuged
   at 900 rpm for 5 min and the supernatant was removed. The cells were
   washed with 5 mL of DPBS. After washing, the cells were centrifuged and
   resuspended in a 1× binding buffer to achieve a density of 5 × 10^5
   cells per mL. Then, 195 µL of the cell suspension was transferred to a
   1.5 mL microcentrifuge tube. Next, 5 µL of annexin-V FITC solution was
   added to the microcentrifuge tube and the cell suspension was incubated
   for 10 min at room temperature. The cell suspension was then
   centrifuged for 5 min at 900 rpm, and the supernatant was removed. The
   cell pellet was resuspended in 190 µL of a 1× binding buffer, and 10 µL
   of propidium iodide (PI) was added for detecting dead cells in the
   sample. Finally, the cell suspension was transferred to a 5 mL test
   tube followed by the addition of a 1× binding buffer to achieve a final
   volume of 500 µL. The samples were then analyzed with a flow cytometer
   to measure green (excitation: 488 nm; emission: 520 nm) and red
   (excitation: 561 nm; emission: 586 nm) fluorescence. The flow cytometry
   gates for four different cell subpopulations were determined as (I)
   FITC^-/PI^- (II) FITC^+/PI^- (III) FITC^+/PI^+, and (IV) FITC^-/PI^+,
   representing live, early apoptotic, late apoptotic, and dead cells,
   respectively. Untreated live cells and ethanol-treated cells were used
   as negative and positive controls to determine the gates.

4.6. Clonogenic Survival Assay

   Cells surviving the VEM treatment were serially diluted by transferring
   1 mL of the cell suspension to a 15 mL centrifuge tube containing 9 mL
   of a fresh growth medium (i.e., a 10-fold serial dilution). Then, 3 mL
   of diluted cell suspensions was transferred to the wells of a 6-well
   plate. The cells were cultured for 12 days for colony formation while
   the growth medium was replaced every 3–4 days. After 12 days, the
   growth medium was removed and the cells were washed with 3 mL of DPBS.
   The cells were then fixed with 1 mL of a fixing agent (methanol: acetic
   acid at 3:1) for 5 min. After the cells were fixed, they were stained
   with crystal violet (0.5%) for 15 min to visualize and to count the
   colonies.

4.7. Cell Count with a Flow Cytometer

   After VEM treatment, the live cells were collected and washed with DPBS
   twice and resuspended in DPBS. Then, 1 mL of the cell suspension was
   transferred to a 1.5 mL microcentrifuge tube. The cells were stained
   with 0.25 µM SYTOX green (catalog # S7020, Thermo Fisher Scientific,
   Waltham, MA, USA) and SYTO60 red (catalog # S11342, Thermo Fisher
   Scientific), followed by incubation at 37 °C for 15 min. Then, the
   cells were transferred to a 5 mL test tube and analyzed with a flow
   cytometer to measure green (excitation: 488 nm; emission: 520 nm) and
   red (excitation: 561 nm; emission: 586 nm) fluorescence. SYTOX green is
   cell impermeant and can only diffuse through a dead cell membrane while
   SYTO60 is cell permeant and can freely diffuse through both live and
   dead cell membranes. Untreated and ethanol-treated dead cells were used
   as negative and positive controls.

4.8. Cancer Stem Cell Markers

   Cells during VEM treatment in flasks were detached and collected at
   desired time points and centrifuged at 900 rpm for 5 min. The
   supernatant was removed, and the cell pellet was washed with 5 mL of
   DPBS. Then, 1 × 10^6 cells were resuspended in 100 µL of a cell stain
   buffer (catalog# 554657) in a microcentrifuge tube. Next, 20 µL of
   PE-conjugated antibodies (CD271 (catalog# 557196), CD44 (catalog#
   555479), or CD34 (555822); BD Biosciences, San Jose, CA, USA) or
   isotype controls were added to the cell suspensions and the suspensions
   incubated for 30 min in dark at room temperature. Following the
   incubation, the cells were centrifuged at 900 rpm for 5 min and the
   supernatant was discarded. Finally, the cells were resuspended in 500
   µL of a cell stain buffer and transferred to a 5 mL test tube. The
   cells were then stained with 0.25 µM SYTOX green for 15 min at room
   temperature and analyzed with a flow cytometer to measure green
   (excitation: 488 nm; emission: 520 nm) and red (excitation: 561 nm;
   emission: 586 nm) fluorescence, respectively.

4.9. ALDEFLUOR Assay

   At desired time points, cells during VEM treatment were detached,
   collected, and centrifuged at 900 rpm for 5 min. The supernatant was
   removed, and the cell pellet was washed with 5 mL of DPBS. The cells
   were then resuspended in ALDEFLUOR buffer to obtain a density of 1 ×
   10^6 cells per mL. Then, 1 mL of the cell suspension was transferred to
   a 1.5 mL microcentrifuge tube and 5 µL of activated ALDEFLUOR reagent
   was added to the cell suspension. After the cell suspension was mixed,
   half of it was transferred to a new microcentrifuge tube and
   immediately treated with 5 µL of diethylamino-benzaldehyde (DEAB). This
   sample was used as a negative control as DEAB inhibits ALDH activity.
   After the samples were incubated for 45 min at 37 °C, the cells were
   centrifuged at 900 rpm for 5 min and the supernatant was removed. The
   cell pellet was then resuspended in ALDEFLUOR buffer at 4 °C,
   transferred to a 5 mL test tube, and stained with 1.5 µM PI for 10 min.
   Finally, the cells were analyzed with a flow cytometer to measure green
   (excitation: 488 nm; emission: 520 nm) and red (excitation: 561 nm;
   emission: 586 nm) fluorescence, respectively.

4.10. Cell Proliferation Assay

   A cell proliferation assay was conducted with the CellTrace
   proliferation kit (catalog# [177]C34570, Thermo Fisher Scientific)
   following the protocol provided by the vendor. A375 cells were
   suspended in DPBS to attain a cell density of 1 × 10^6 cells per mL.
   Then, 1 µL of carboxyfluorescein succinimidyl ester (CFSE) dye was
   added to 1 mL of the cell suspension and the cells were incubated at
   room temperature for 20 min. After incubation, DMEM medium was added to
   the cell suspension to stop the staining and the cells were centrifuged
   at 900 rpm for 5 min. The supernatant was removed, and the pellet was
   resuspended in fresh DMEM medium. Approximately 3 × 10^5 of
   CFSE-stained cells were plated in each well of a 6-well plate and
   incubated for 24 h. After 24 h, the cells were either treated with 10
   µM of VEM or left untreated. At indicated time points, cells were
   collected, centrifuged, and resuspended in 1 mL of DPBS. The cells were
   then stained with 1.5 µM of PI to detect dead cells. The cells were
   transferred to a 5 mL test tube and analyzed with a flow cytometer to
   measure green (excitation: 488 nm; emission: 520 nm) and red
   (excitation: 561 nm; emission: 586 nm) fluorescence, respectively.

4.11. Metabolomics

   Cells were treated with VEM in T-75 flasks for 3 days. After 3 days,
   the surviving cells were collected, washed with 5 mL of DPBS twice, and
   pooled in a 1.5 mL micro centrifuge tube. The final cell pellet volume
   for each group was ~100 µL. The cell pellet was first flash-frozen in a
   dry ice/ethanol bath and then stored in −80 °C before the sample was
   shipped to Metabolon, Inc. (Morrisville, NC, USA). Cells treated with
   the solvent (DMSO) only were used as a control group. A metabolomics
   study including sample extraction, instrumentation, and initial data
   analysis was conducted according to Metabolon’s protocols [[178]60].
   The mass spectrometry data were normalized to the protein concentration
   (assessed by Bradford assay). The normalized data were used for
   unsupervised hierarchical clustering with the Clustergram function of
   MATLAB. An ANOVA test was used for pairwise comparisons (p < 0.05), and
   a Q-value for each metabolite was assessed to estimate the false
   discovery rate [[179]60]. Enrichment analysis was performed using the
   overrepresentation analysis (ORA) algorithm of MetaboAnalyst [[180]27].
   The metabolites that were significantly different in VEM persisters
   compared to those in the control group were clustered into two groups:
   upregulated and downregulated metabolites. The list of compound names
   (human metabolome database ID) for each group was used as an input for
   the enrichment analysis, which is based on several libraries containing
   ~9000 biologically meaningful metabolite sets. ORA uses hypergeometric
   test to evaluate if a specific metabolite set or pathway is truly (not
   by chance) represented within the input list. Finally, the results were
   provided as dot plots, where the size of the circle represents the
   enrichment ratio (observed hits/predicted) and the color represents the
   p-value for each metabolite set [[181]61].

4.12. Mitoplate Assays

   Mitoplate assays were performed following the protocol provided by
   Biolog, Inc. [[182]62]. After VEM treatment, the cells were collected,
   resuspended in a fresh drug-free growth medium, and incubated for 24 h.
   After incubation, the cells were collected and washed with DPBS twice.
   The cells were then suspended in a 1× Biolog mitochondrial assay
   solution (BMAS, catalog# 72303, Biolog, Inc.) to obtain a cell density
   of 1 × 10^6 cells per mL. For assessing the mitochondrial activity, an
   assay mixture containing 2× BMAS, a tetrazolium-based 6× dye mix
   (catalog# 74353, Biolog, Inc.), saponin (960 µg/mL), and sterile
   deionized (DI) water in a ratio of 6:4:1:1 was prepared and 30 µL of
   the assay mixture was pipetted into each well of the mitoplate
   containing various TCA cycle substrates. The plate was then incubated
   for 1 h at 37 °C to completely dissolve the substrate. Finally, 30 µL
   of the cell suspension in 1× BMAS was added to each well of the
   microarray. To assess the rate of consumption of these substrates,
   optical density at 590 nm (OD[590]) was measured with Varioskan Lux
   Microplate Reader (catalog# VLBL00GD0, Thermo Fisher Scientific) every
   10 min for 100 min.

4.13. PM-M1 Assays

   PM-M1 assays were performed using a protocol provided by Biolog, Inc.
   [[183]62]. After VEM treatment, the cells were collected; resuspended
   in a fresh, drug-free growth medium; and incubated for 24 h. At 24 h,
   the cells were washed with 5 mL of DPBS twice. The cell pellet was
   resuspended in Biolog IF-M1 medium (catalog# 72301, Biolog, Inc.)
   supplemented with penicillin/streptomycin, 5% FBS, and 0.3 mM glutamine
   to obtain a cell density of 4 × 10^5 cells per mL. Then, 50 µL of the
   cell suspension was transferred to each well of the PM-M1 plate and
   incubated at 37 °C for 48 h. At desired time points (t = 0 h, 24 h, and
   48 h), 10 µL of the tetrazolium-based dye (catalog# 74352, Biolog,
   Inc.), was added to each well of the PM-M1 plate and incubated for 8 h.
   The rate of dye reduction was evaluated by measuring absorbance at 590
   nm (OD[590]) every 30 min. The absorbance readings are subtracted by
   the baseline (i.e., initial absorbance at t = 0 min) to determine the
   absolute absorbance change for each substrate. These data are then
   normalized by subtracting control (glutamine only) measurements.

4.14. Glucose and Lactate Consumption Assay

   After VEM treatment, cells were collected and resuspended in Biolog
   IF-M1 medium (catalog# 72301, Biolog, Inc.) supplemented with
   penicillin/streptomycin, 5% FBS, and 0.3 mM glutamine. When indicated,
   4 mM sodium lactate and/or 4 mM glucose were added to the cell
   suspension. The cell density was adjusted to 4 × 10^5 cells per mL.
   Then, 500 µL of the cell suspension was transferred to each well of a
   24-well plate and incubated at 37 °C. At desired time points (t = 24 h
   and 48 h), the cell suspension was removed and centrifuged at 900 rpm
   for 5 min and the supernatant was transferred to a 1.5 mL
   microcentrifuge tube. The glucose and lactate concentrations in samples
   and standard solutions were measured using a glucose colorimetric
   detection kit (catalog# EIAGLUC, Thermo Fisher Scientific) and a
   lactate assay kit (catalog# MAK064-1KT, Sigma Aldrich) following the
   vendor’s protocol. For the lactate assay, the supernatant was
   deproteinized with a 10 kDa MWCO spin filter. This additional step was
   needed as the presence of lactate dehydrogenase can degrade lactate and
   interfere with the readings. Standard curves were used to calculate the
   amount of glucose or lactic acid consumed by the cells daily. The data
   were then normalized by the number of cells.

4.15. Viability Assay in a Minimal Medium

   After VEM treatment, cells were collected and resuspended in Biolog
   IF-M1 medium (catalog# 72301) supplemented with
   penicillin/streptomycin, 5% FBS, and 0.3 mM glutamine. The cell density
   was adjusted to 4 × 10^5 cells per mL. The cell suspension was further
   supplemented with 4 mM glucose and/or 4 mM sodium lactate. Then, 500 µL
   of the cell suspension was transferred to each well of a 24-well plate
   and incubated at 37 °C. At t = 48 h, the cells were collected and
   resuspended in 500 µL of DPBS. The cells were stained with 0.25 µM
   SYTOX green and SYTO60 red and incubated for 15 min at room
   temperature. Finally, the cells were transferred to a 5 mL test tube
   and analyzed with a flow cytometer to measure green (excitation: 488
   nm; emission: 520 nm) and red (excitation: 561 nm; emission: 586 nm)
   fluorescence. The live and dead cells were separated based on their
   fluorescence intensity, and the number of live cells were enumerated by
   the flow cytometer.

4.16. Statistical Analysis

   Unequal variance t-test or ANOVA was used for pairwise comparisons (p <
   0.05). For PM-M1 assays, substrates whose absorbance was found to be
   higher than that of the no-substrate control were selected for linear
   regression analysis. The slopes of untreated and treated groups for the
   selected substrates were compared with F statistics using GraphPad
   Prism 8.3.0, and the threshold of significance was set to p < 0.05. A
   minimum of three independent biological replicates were performed, and
   data points in figures denote the mean value ± standard error.

Acknowledgments