Transcriptome-wide analysis of the differences between MCF7 cells cultured in DMEM or αMEM

Yang Jiao; Hongbo Zhao; Lin Lu; Xiangyu Zhao; Yanchun Wang; Bingrong Zheng

doi:10.1371/journal.pone.0298262

. 2024 Mar 28;19(3):e0298262. doi: 10.1371/journal.pone.0298262

Transcriptome-wide analysis of the differences between MCF7 cells cultured in DMEM or αMEM

Yang Jiao ^1,^2,^#, Hongbo Zhao ^3,^#, Lin Lu ^2,^#, Xiangyu Zhao ⁴, Yanchun Wang ², Bingrong Zheng ^5,^*

Editor: Sadiq Umar⁶

PMCID: PMC10977736 PMID: 38547234

Abstract

MCF7 cells have been used as an experimental model for breast cancer for decades. Typically, a culture medium is designed to supply cells with the nutrients essential for their continuous proliferation. Each medium has a specific nutritional composition. Therefore, cells cultured in different media may exhibit differences in their metabolism. However, only a few studies have investigated the effects of media on cells. In this study, we compared the effects of Dulbecco’s modified Eagle medium (DMEM) and minimum essential medium alpha modification (αMEM) on MCF7 cells. The two media differentially affected the morphology, cell cycle, and proliferation of MCF7 cells, but had no effect on cell death. Replacement of DMEM with αMEM led to a decrease in ATP production and an increase in reactive oxygen species production, but did not affect the cell viability. RNA-sequencing and bioinformatic analyses revealed 721 significantly upregulated and 1247 downregulated genes in cells cultured in αMEM for 48 h compared with that in cells cultured in DMEM. The enriched gene ontology terms were related to mitosis and cell proliferation. Kyoto encyclopedia of genes and genomes analysis revealed cell cycle and DNA replication as the top two significant pathways. MCF7 cells were hypoxic when cultured in αMEM. These results show that the culture medium considerably affects cultured cells. Thus, the stability of the culture system in a study is very important to obtain reliable results.

Introduction

Breast cancer is the most prevalent cancer in women. With a global incidence of 24.2%, breast cancer ranked first among cancer types in women in 2018 [1]. Basic cancer research has mainly used cell lines as the main experimental model. Cultured cells have led to major discoveries in various fields of cancer research, including those related to the occurrence and development of cancers [2], anticancer treatment [3], and prognosis [4]. Approximately 84 human breast cancer cell lines have been classified by molecular subtyping into five subtypes: luminal A, luminal B, HER-2⁺, triple⁻ A, and triple⁻ B [5]. Each cell line is cultured in a standard medium. MCF7 cells are of the luminal A subtype and are cultured in Eagle’s minimum essential medium (EMEM) with 0.01 mg/mL human recombinant insulin and 10% fetal bovine serum (FBS) according to the guidelines of the American Type Culture Collection (ATCC) [6]. However, in some laboratories, they are cultured in Dulbecco’s modified Eagle medium (DMEM) containing 10% FBS [7–11]. In our laboratory, we have been culturing this cell line in DMEM since we received it (at least 15 years ago) from a laboratory where this cell line was also cultured in DMEM. Therefore, we considered DMEM as the usual medium for MCF7 cells. The culture medium should not be changed during an experiment, especially when seeding cells, as the cells would otherwise be subjected to stress resulting from nutritional changes [12]. Cells may finally adapt to the new environment over time, but their metabolic and gene expression profiles are likely to be modified during this period. For example, when breast cancer cell lines were separately cultured in three culture media for four passages, their phenotypic differentiation markers differed and the expression of these markers depended on the composition of the medium [13]. When cancer cells are cultured with excessive concentrations of pyruvate, their proliferation depends less on mitochondrial respiration compared with that of cells cultured with a regular concentration of pyruvate [14]. Therefore, we wanted to check if temporarily replacing DMEM with other media would affect the cells.

In conventional cell culture, the culture medium is designed to supply cells with the nutrients essential for continuous proliferation [15]. Currently, DMEM and minimum essential medium alpha modification (αMEM) are the widely used cell culture media. Each medium has a specific formulation. DMEM is a universally used culture medium for various primary cell types and immortal cell lines. αMEM is enriched with non-essential amino acids and additional vitamins [16]. In this study, we cultured MCF7 cells in DMEM or αMEM and compared their gene expression and metabolic profiles. We aimed to comprehensively investigate the effects of the culture medium stability on cultured cells.

Materials and methods

Cell culture

The breast cancer cell line MCF7 used in this study was obtained from the Kunming Cell Bank of the Chinese Academy of Sciences. It was maintained in DMEM supplemented with 10% FBS without heat inactivation (10270–106, Gibco, Life Technologies™, Australia), 100 mg/L penicillin, and 100 mg/L streptomycin (15140–122, Gibco, Life Technologies™, NY, USA) at 37°C with 5% CO₂. DMEM contains 4.5 g/L glucose, L-glutamine, and 110 mg/L sodium pyruvate (C11995500BT; Gibco, Thermo Fisher Scientific, Suzhou, China).

Exposure of MCF7 cells to a different medium

MCF7 cells were seeded at a density of 1 × 10⁵ cells/mL per well in a 6-well plate (3516, Corning, NY, USA) and cultured overnight in DMEM. Subsequently, the medium in the treatment group was replaced with 2 mL of αMEM, supplemented with 10% FBS without heat inactivation, 100 mg/L penicillin, and 100 mg/L streptomycin (Gibco by Life Technologies™, NY, USA). αMEM contained L-glutamine, Ribonucleosides and Deoxyribonucleosides (SH30265.01; Hyclone, Thermo Scientific, Beijing, China). The medium in the control group was replaced with 2 mL of fresh DMEM.

Flow cytometric analysis of the cell cycle

Control MCF7 cells and those cultured in αMEM for 48 h were collected after digestion with trypsin without EDTA (T1350, Solarbio, Beijing, China) and fixed overnight in ice-cold 70% ethanol. The fixed cells were stained with 10 μL propidium iodide (PI, CW2574S, CWBIAO, Beijing, China) in phosphate-buffered saline (PBS) containing 0.1% Triton X-100 (T8200, Solarbio, Beijing, China) and 50 μg/mL RNase A (CW0601, Beijing, China) and analyzed using the CyFlow Space (Partec) and FolMax 2.82 software.

Annexin V-FITC/PI staining

The percentage of apoptotic cells was determined using an Annexin V-FITC/PI Apoptosis Detection Kit (CW2574S, CWBIO, Beijing, China). Briefly, control MCF7 cells and those cultured in αMEM for 48 h were collected after digestion with trypsin without EDTA and then washed with cold PBS and resuspended in the binding buffer at a concentration of 10⁶ cells/mL. The cells were incubated at 37°C with 5 μL of Annexin V-fluorescein isothiocyanate (FITC) and 10 μL of PI for 10 min and analyzed using the CyFlow Space (Partec) and FolMax 2.82 software.

Cell attachment assay

MCF7 cells were digested with trypsin and centrifuged in two tubes. The cell pellet was resuspended separately in DMEM and αMEM, and 1×10⁴ cells were seeded per well in a 96-well plate after counting. The wells were washed with PBS to remove nonadherent cells, and then 100 μL of fresh medium and 20 μL of CellTiter 96 Aqueous One Solution Reagent were added to detect cell viability at 15, 30, 45, 60, and 75 min.

Colony formation assay

Cells in logarithmic growth phase were collected after trypsin digestion, resuspended in culture medium, and counted. These cells were inoculated in a six-well plate (1000 cells per well), and 2 mL αMEM or DMEM was added to the treatment and control groups, respectively. The medium was refreshed every three days, and the cells were cultured for 3 weeks when the majority of colonies had more than 10 cells. The cells were washed once with PBS. One milliliter of 4% paraformaldehyde was added to each well and the cells were fixed for 30 min. The cells were washed once with PBS and then stained with 1 mL of crystal violet added to each well for 15 min. After washing the cells three times with PBS, they were air-dried and photographed, and the number of clones was counted. The colony formation rate was calculated using the following equation:

Clone formation rate = (number of clones/number of inoculated cells) ×100%

ATP detection

The Mitochondrial ToxGlo^TM Assay (Promega, Madison, WI, USA) was used to detect intracellular ATP levels in MCF7 cells. The experiment was performed following the steps prescribed in the technical manual provided by the manufacturer. Briefly, MCF7 cells were seeded at a density of 5×10³ cells/well in a 96-well plate (3599, Corning) containing 100 μL DMEM and cultured overnight. Subsequently, the medium was replaced with 100 μL αMEM or DMEM for the treatment and control groups, respectively. At the detection time points, the cells were washed with glucose-free culture medium twice, and then 80 μL glucose-free culture medium and 20 μL of 5× Cytotoxicity Reagent were added to each well. The plates were incubated at 37°C for 30 min, and then at 25°C for 5 min. Subsequently, 100 μL ATP Detection Reagent was added to each well and the luminescence generated was measured.

ROS and cell proliferation assays

The ROS-Glo^TM H₂O₂ Assay (Promega) was used to detect the levels of reactive oxygen species (ROS). The experiment was performed following the steps prescribed in the technical manual provided by the manufacturer. Briefly, MCF7 cells were seeded at a density of 5×10³ cells/well in a 96-well plate (3599, Corning) containing 100 μL DMEM and cultured overnight. Subsequently, the medium was replaced with 80 μL αMEM for the treatment group or with 80 μL fresh DMEM for the control group. The H₂O₂ substrate solution (20 μL) was added to the wells at 0, 18, and 42 h, and plates were further incubated at 37°C with 5% CO₂ for 6 h. The entire medium (100 μL) in the wells was transferred to a new well, and 100 μL of ROS-Glo^TM Detection Solution was added to each well. The plate was incubated for 20 min at 25°C and subsequently relative luminescence units were recorded. Simultaneously, 100 μL fresh medium was added to the original assay well along with 20 μL of CellTiter 96 Aqueous One Solution Reagent, and the plate was incubated at 37°C in a 5% CO₂ incubator. After 3 h, the absorbance of each sample was recorded at 490 nm.

RNA isolation and RNA-Seq library preparation

Control MCF7 cells and those cultured in αMEM (10⁶ cells/mL) for 48 h were harvested (three biological replicates per sample), and their total RNA was extracted using TRIzol™ reagent (93289, Invitrogen, Carlsbad, USA). The RNA quality and quantity were determined using the RNA Nano 6000 Kit in the Agilent 2100 Bioanalyzer System, and the samples were stored at –80°C until needed. For construction of cDNA libraries, 10 μg total RNA per sample was used. A total of six samples were sequenced using the BGISEQ-500 platform.

On average, approximately 23.94 Mb clean reads (S1 Table) were generated per sample, and 18,174 genes were detected. The average mapping ratio of clean reads to the reference human genome was 94.82% and the uniformity of the mapping results per sample suggested that the two groups were comparable. Raw reads were filtered using the internal software, SOAPnuke, to obtain clean reads [17]. The clean reads were mapped to reference transcripts (Human hg19) using Bowtie2 [18].

Differential gene expression and gene enrichment analysis

Gene expression was expressed as the number of uniquely mapped reads per kilobase of exon fragments per million mappable reads (FPKM) with RSEM [19]. To reflect the gene expression correlation between samples, we calculated the Pearson correlation coefficients for all gene expression levels between each pair of samples and reflected these coefficients in the form of heat maps, as shown in S1 Fig. We then performed a principal components analysis (PCA) based on the PCA plan, as shown in S2 Fig.

Based on the gene expression levels, the differentially expressed genes (DEGs) were identified using the DEGseq algorithm [20]. For the analysis, a q-value ≤0.001 and an absolute value of log₂ ratio ≥1 were used to verify the significance of differences in gene expression between the two samples. Based on the DEGs, pathway function analysis was performed using the clusterProfiler package [21]. Enrichment analysis was carried out using the hypergeometric test with a threshold value of 0.05 based on the Kyoto encyclopedia of genes and genomes (KEGG) database.

Validation of sequencing-based gene expression levels via quantitative real-time polymerase chain reactions (qPCR)

Total RNA from control MCF7 cells and those cultured in αMEM for 48 h was extracted using the TRIzol™ reagent (93289, Invitrogen). The quality and quantity of the RNA samples was determined using a Nano-300 spectrophotometer (Allsheng). The samples were used to synthesize the first-stand cDNA using the PrimeScript™ RT Reagent Kit with gDNA Eraser according to the manufacturer’s instructions (RR047A, Takara, China). The primer sequences (Table 1) were designed using PrimerQuest (http://www.idtdna.com/primerquest/Home/Index). qPCR was performed using the BIO-RAD CFX96™ Real-Time System and FastStart Universal SYBR Green Master (06924204001, Roche, Mannheim, Germany). Relative quantification was performed using the comparative Ct (2^−△△Ct) method.

Table 1. Sequences of the primers used in the quantitative real-time polymerase chain reactions.

Primers	NCBI ID	Primer sequences
P21	NM_000389	S:5′ `TTAGCAGCGGAACAAGGAGTCAGA`3′ A:5′ `ACACTAAGCACTTCAGTGCCTCCA` 3′
CDK1	NM_001170406.1	S:5′`GCCTGAGATAACATAGAACTGGTAG3`′ A: 5′`CTCTGCCCTAGGCTTTCATTAC` 3′
GAPDH	NM_002046.7	S: 5′`GGTGTGAACCATGAGAAGTATGA` 3′ A: 5′`GAGTCCTTCCACGATACCAAAG` 3′
BIRC3	NM_001165.4	S: 5′ `CAAGCCAGTTACCCTCATCTAC` 3′ A: 5′ `CTGAATGGTCTTCTCCAGGTTC` 3′
ITGA1	NM_181501.2	S: 5′ `GACTGGCTTCAGTGCTCATTA` 3′ A: 5′ `TTGACTAGCCTTCTGCATGAC` 3′
β-actin	NM_001101.5	S: 5′ `TGACGTGGACATCCGCAAAG` 3′ A: 5′ `CTGGAAGGTGGACAGCGAGG` 3′

Open in a new tab

Western blot analysis

MCF7 cells cultured in DMEM or αMEM for 48 h were lysed in 50 μL RIPA lysis buffer (strong) (P0013B, Beyotime, Shanghai, China) containing 0.5 μL phenylmethylsulphonyl fluoride (ST506, Beyotime), and the lysates were incubated on ice for 30 min. The lysates were then incubated with 50 μL of 2X SDS-PAGE protein loading buffer (Bio-Rad) in boiling water for 10 min. The supernatant was subjected to electrophoresis on a 10% sodium dodecyl sulfate-polyacrylamide gel and the resolved proteins were transferred onto polyvinylidene difluoride membranes (IPVH00010, Merck Millipore). The membranes were blocked with TBST (0.01 M Tris-buffered saline (TBS) with 0.1% Tween-20, pH 7.4) containing 5% non-fat dried milk for 1 h and incubated overnight at 4°C with antibodies against GAPDH (RRID: AB_2801390, CW0100M, 1:2000; CWBio, Jiangsu, China), P21 (RRID: AB_10860537, ab109520, 1:500, abcam, Shanghai, China), CDK1 (RRID: AB_11218160, AM06438SU-N, 1:100; Origene, Wuxi, China), and β-actin (RRID: AB_2665433, CW0096M, 1:1000; CWBio, Jiangsu, China). The membranes were then incubated with horseradish peroxidase-conjugated goat anti-mouse IgG (RRID: AB_2736997, CW0102S, CWBio, Jiangsu, China) or goat anti-rabbit IgG (RRID: AB_2814709, CW0103, 1:2000; CWBio, Jiangsu, China) at 20–25°C for 1 h and then with the ECL substrate solution (CW0049S, 1:1 [v/v]; CWBio, Jiangsu, China). The bands were got from BioRed gel imaging system (Model No. PowerPac Universal Power Supply) with Image Lab 5.2 system. The protein bands quantified using Photoshop 7.0.

Statistical analyses

Statistical analyses were performed using Microsoft Excel 2007 and R 4.2.3. Graphs were drawn using the GraphPad Prism 5 software and R 4.2.3. A value of P < 0.05 was considered to indicate a statistically significant difference.

Results

Effect of culture medium on cell cycle and proliferation

To study the effect of culture medium on cells, we cultured MCF7 cells in DMEM or αMEM with 10% FBS. MCF7 cells cultured in DMEM displayed the characteristic “cobblestone” morphology with a clear boundary and were tightly packed and flat. However, the cells cultured in αMEM for 48 h displayed groups of irregular cells showing cell-to-cell connections (Fig 1; marked with red arrow). We evaluated the cell cycle distribution of MCF7 cells cultured in DMEM and αMEM for 24 and 48 h using PI staining. No obvious changes were noted at 24 h; however, at 48 h, the number of cells in the G0/G1 and G2/M phases decreased and increased significantly, respectively (Fig 2). As evident from the results of Annexin V/PI staining, there was no significant difference in cell death between the two groups (Fig 3). Next, we measured the ability of cells to attach to the surface of the cell culture flasks in the two culture media. The MCF7 cells in DMEM adhered to the flask surface more rapidly (45 min) than they did in αMEM (60 min) (Fig 4). The ability to adhere to the flask surface reflects the survival of the cells after seeding. However, not every adherent cell proliferates or forms a clone. Formation of colonies requires both cell adhesion and proliferation. Therefore, we tested the colony-forming ability of the cells. The rate of colony formation in MCF7 cells cultured in DMEM was 40.07 ± 3.63% (Fig 5). However, in αMEM, although cell adhesion was observed 24 h after seeding, the cells gradually died upon culture and there were no surviving cells at the time of harvesting. This indicated that the proliferation activity of MCF7 cells was affected in αMEM.

Fig 1 — Images were obtained after 48 h of culture in DMEM or αMEM. Representative micrographs from at least three independent experiments are shown. All the images were acquired at 20× magnification.

Fig 2 — A. Flow cytometry results. Cells were collected after 24 h or 48 h cultured in DMEM or αMEM and stained with PI. B. Statistical chart of cell cycle. Data were presented as the mean ± S.D. from three independent experiments.

Fig 3 — A. Apoptotic status. MCF7 cells were collected after 48 h cultured in DMEM or αMEM. The cultured cells were stained with 5 μL Annexin V-FITC and 10 μL PI. The cells in Q1, Q2, Q3, and Q4 quadrants are necrotic, late-apoptotic, viable cells, and early-apoptotic, respectively. B. Quantitative analysis for cell apoptosis rate. The results are presented as the mean ± S.D. from three independent experiments.

Fig 4 — The X-axis represents the cell adhesion time. The Y-axis represents cell viability.

Fig 5 — A. Clonal plaques. Cells were inoculated in a six-well plate (1000 cells per well), and 2 mL αMEM or DMEM was added to the treatment and control groups, respectively. The medium was refreshed every three days, and the cells were cultured for 3 weeks and stained with crystal violet. B. Statistical chart of Colony forming assay. Clone formation rate = (number of clones/number of inoculated cells) ×100%. The results are presented as the mean ± S.D. from three independent experiments.

Effect of culture medium on ATP and ROS production

ATP is the most important energy molecule in cells and is a key substance for maintaining normal cellular activity. In standard glucose-containing culture media, propagated cells tend to use glycolysis to meet their ATP needs. We investigated whether a change in the culture medium would lead to changes in intracellular ATP levels, thereby, affecting cell growth. Replacement of DMEM (high sugar) with αMEM led to a decrease in ATP production in MCF7 cells (Fig 6A). Simultaneously, ROS production continued to increase (Fig 6B). However, during this process, there was no significant difference in cell viability (Fig 6C).

Fig 6 — A. Intracellular ATP levels assay. B. ROS assay. C. Cell viability assay. Intracellular ATP levels and ROS levels were detected at 6 h, 24 h and 48 h after replacement of DMEM with αMEM. At the same time, cell viability was detected. Data were presented of three independent experiments.

Identification of DEGs in cells cultured in different media

According to the results of RNA-seq (The mRNA-seq data from this study has been deposited in the NCBI sequence read archive under the BioProject number PRJNA779251 (https://www.ncbi.nlm.nih.gov/bioproject/PRJNA779251/), with the fq files spanning accession numbers SRR16914480-SRR16914481) and bioinformatics analysis, a total of 721 up- and 1247 downregulated genes were identified [|log2 (fold change) | >1, q-value ≤0.001] (Fig 7).

Fig 7 — The X-axis represents value A (log2-transformed mean expression level). The Y-axis represents value M (log2-transformed fold change). Red and blue dots represent up- and down-regulated DEGs, respectively. Gray points represent non-DEGs. Cells were collected after 48 h cultured in DMEM or αMEM. n = 3 in each medium.

Next, we performed GO classification and functional enrichment analyses of the DEGs. The DEGs were assigned three ontologies: biological processes (BP), cellular component (CC), and molecular biological function (MF). The top-10 enriched terms for each ontology are shown in Fig 8. All the terms were closely related to mitosis, consistent with the proliferating state of the cells. The culture medium affected cell cycle and proliferation, consistent with the results of cell viability and cell cycle analyses.

Fig 8 — BP: Biological processes. CC: Cellular components. MF: Molecular function. The X-axis refers to the number of genes in functional analysis. The Y-axis refers to GO terms. The colors, ranging from blue to red, refer to the change in value threshold of the identified significantly enriched GO terms (P-adjust < 0.05) from low to high.

To identify the biological functions associated with the DEGs, we performed KEGG pathway analysis (Fig 9), which revealed 19 significant pathways (p < 0.05). “Cell cycle” and “DNA replication” were the top-two terms, which confirmed that the culture medium affected the cell cycle and proliferation of MCF7 cells.

Validation of the sequencing results by determining the gene expression levels

Among the DEGs, P21, GAPDH, and BIRC3, were significantly upregulated, whereas CDK1 and ITGA1 were significantly downregulated (Table 2). To validate these gene expression patterns, we assessed their mRNA levels using qPCR and observed that the qPCR results were consistent with the RNA-Seq results (Fig 10).

Table 2. List of differentially expressed genes in MCF7 cells cultured in αMEM vs. DMEM.

Symbol	Gene ID	Length (bp)	C1 Expression level	C2 Expression level	log₂ ratio (C2/C1)	q-value
P21	1026	2138	21568	54319	1.32	0
GAPDH	2597	1421	242199	514444	1.07	0
BIRC3	330	5174	227.6	2297.57	3.33	0
CDK1	983	1924	4011	1791	–1.17	7.03E-194
ITGA1	3672	4811	22	6	–1.88	0.00099935

Open in a new tab

C1 expression level: Gene expression level in MCF7 cells cultured in DMEM.

C2 expression level: Gene expression level in MCF7 cells cultured in αMEM.

log2FoldChange(C2/C1): The log2 value of ratio of C1-Expression to C2-Expression.

q-value: Adjusted p-value.

Fig 10 — Data are presented as Ct(2^-△△Ct) relative to the control level. Cells were collected after 48 h cultured in DMEM or αMEM. Data are presented as mean ± S.D. of three independent experiments. *P < 0.05, **P < 0.01, ***P < 0.001.

To evaluate the levels of protein encoded by the DEGs, we performed western blot analysis of proteins extracted from MCF7 cells cultured in DMEM or αMEM. The P21 and GAPDH levels were significantly increased, whereas CDK1 levels were significantly decreased at 24 h. At 48 h, the P21 and CDK1 levels showed no obvious changes, but GAPDH levels were increased (Fig 11).

Fig 11 — A. Western blot results. B. Quantitation of the results. Cells were collected after 24 h or 48 h cultured in DMEM or αMEM. Data are presented as mean ± S.D. of three independent experiments. Gray value ratio = the gray value of the target band/the gray value of the internal reference band. *P < 0.05, **P < 0.01, ***P < 0.001.

Discussion

Each cell line required a specific medium for its optimal culture. MCF7 cells are generally cultured in DMEM supplemented with 10% FBS [7–10]. To evaluate the effect of culture medium on cells, we cultured MCF7 cells in two different media (DMEM and αMEM supplemented with 10% FBS). After 48 h of culture, the cells cultured in αMEM exhibited a different morphology, cell cycle, and proliferation compared with those cultured in DMEM; however, there was no significant difference in cell death. Upon replacement of DMEM with αMEM, the ATP production in MCF7 cells decreased, and ROS production increased but there was no significant difference in cell viability. To evaluate the changes in gene expression, we performed RNA-Seq analysis of MCF7 cells cultured in each medium. A total of 721 genes were significantly upregulated and 1247 genes were significantly downregulated in MCF7 cells cultured in αMEM compared with those cultured in DMEM. These results indicate that the medium change had a significant effect on the growth of MCF7 cells. Therefore, stable culture conditions are crucial for the stability and reliability of experimental results, especially for high-throughput sequencing analysis.

To decipher the changes in MCF7 cells caused due to change in the culture medium, we performed RNA-Seq analysis and subjected the data to bioinformatic analysis. The results showed that differential gene enrichment of biological processes was mainly related to DNA replication and chromosome segregation. The enrichment of cellular components was mainly related to chromosome concentration, centromere, microtubule, and kinetochore and that of molecular biological functions was mainly related to RNA polymerase II. This enzyme exists in eukaryotic cells and catalyzes the transcription of genes to mRNAs and most hnRNAs and miRNA precursors [22]. All these results suggested that the changes in MCF7 cells cultured in αMEM compared with those cultured in DMEM were related to the G2/M phase of the cell cycle. The G2 phase (second gap phase) encompasses the late stage of DNA synthesis and preparations related to mitosis [23]. During this period, DNA synthesis is terminated, and various genes are expressed, including tubulin and maturation-promoting factors [24]. The M phase is the cell division phase, in which a series of nuclear changes, chromatin condensation, emergence of spindles, and precise and equal distribution of chromosomes into two daughter cells occur [25]. Thus, the results of the GO analysis were consistent with those of the flow cytometric cell cycle analysis.

According to the KEGG analysis results, the top-two pathways to be affected were cell cycle and DNA replication. This directly shows that the change in the culture medium affects the cell cycle and proliferation considerably. Among the DEGs, P21 (cyclin dependent kinase inhibitor 1A, CDKN1A) [26] was upregulated, and CDK1 (cyclin-dependent kinase 1) was significantly downregulated. P21 can inhibit CDK2 [27], CDK1, and CDK4/6 complexes [28] and, thus, functions as a regulator of cell cycle progression in the G1 and S phases. Additionally, P21 blocks cell cycle progression in the S phase by binding to and inhibiting proliferating cell nuclear antigen (PCNA) [29]. P21 is important for the G2/M transition and mitotic progression [30] and maintains chromosomal integrity in vivo. Loss of P21 completely abolishes the cell cycle arrest function of P53R172P and accelerates the onset of tumorigenesis in Trp53^515C/515C mice [31]. In fact, P21 is a two-faced genome guardian that not only inhibits, but also activates the cell cycle, depending on its expression levels [28]. Chien-Hsiang Hsu et al. [32] reported the existence of a “Goldilocks zone” for the effect of P21 on cell proliferation. In our study, the number of cells in the G0/G1 phase decreased and that of cells in the G2/M phase increased concomitantly with the upregulation of P21.

CDK1 is required for the transition of cells from the G2 phase to mitosis [33]. The activity of CDK1 is regulated by cyclins and checkpoint kinases, which ensures that the cells do not enter mitosis with incompletely replicated or damaged DNA [34]. CDK1 overexpression correlates with an adverse prognosis in breast cancer [35]. Cells with inhibited CDK1 expression no longer divide but increase in size [36]. In our study, CDK1 was significantly downregulated in cells cultured in αMEM compared with that in cells cultured in DMEM. Additionally, morphological assessment showed that the intercellular boundary was not clear in cells cultured in DMEM, which indicates that the downregulation of CDK1 interfered with mitosis and cell cycle arrest at the G2/M phase. Recent studies have shown that CDK1 plays a role in regulating the G2/M phase. The activity of CDK1 changes throughout the cell cycle; the CDK1 levels start to increase during the S phase, reach a maximum in the metaphase, and decline rapidly in the anaphase [37]. Katharina et al. [36] reported that CDK1 plays an important role in the translation of 5ʹ TOP mRNAs, which include mRNAs encoding ribosomal proteins and several translation factors. Thus, CDK1 probably regulates cell proliferation by regulating protein synthesis. Furthermore, the cyclin B1/CDK1 complex mediates mitochondrial activity during cell cycle progression, enabling mitochondria to sense cellular fuel demand and coordinate the ATP output [38]. In our study, along with the significant downregulation of CDK1, we found a significant decrease of intracellular ATP levels in αMEM compared with DMEM. In most tissues, inactivation of CDK1 causes remodeling of integrin-receptor adhesion complexes and the actin cytoskeleton; consequently, cells rapidly enter mitosis [39]. Considering the complex and diverse functions of CDK1, additional research is needed to elucidate its role in mediating the effects of culture medium on cells.

Notably, we found the hypoxia-inducible factor 1 (HIF1) signaling pathway, glycolysis/gluconeogenesis pathway, and glutathione metabolism among the enriched KEGG pathways. These three pathways are intrinsically related to hypoxia. HIF1 is a master transcriptional regulator of cellular adaptation to hypoxia [40]. Its activity is significantly increased under hypoxic conditions [41]. The glycolytic pathway, also known as the EMP pathway, involves a series of reactions through which glucose and glycogen can be degraded to pyruvate, along with ATP production. The glycolytic pathway can occur under anaerobic and aerobic conditions and is a common mechanism of glucose metabolism in all organisms [42]. Glutathione (GSH) is a small active peptide present in almost every cell type in the body. It plays important antioxidant and detoxification roles [43]. Under normoxic conditions, oxidative metabolism is the main mechanism of energy production that supports cell survival and development [44]. However, under hypoxia, oxidative metabolism is impaired and there is an accumulation of ROS produced by the electron transport chain. Under such conditions, the HIF1 alpha subunit accumulates and dimerizes with HIF1 beta. This dimer then translocates to the nucleus to activate the transcription of target genes [41], including lactate dehydrogenase (LDHA), which is involved in the glycolytic pathway, and pyruvate dehydrogenase kinase 1 (PDK1). Activated HIF1 can activate the expression of both PDK1 and LDHA [45] to switch cells from oxidative metabolism to glycolytic metabolism [46,47]. In addition to ATP production, the glycolytic pathway prevents ROS accumulation, which may lead to cellular dysfunction and death. In breast cancer cells, hypoxia induces the expression of genes involved in the glutathione biosynthetic pathway, such as SLC7A11, which is a direct target gene of HIF1, and subsequently induces glutathione synthesis [48]. Glutathione is an ROS scavenger that can stoichiometrically reduce NAD(P)H [41]. According to our experiment results, replacement of DMEM (high sugar) with αMEM led to a decrease in ATP production and increase in ROS production. Under hypoxic conditions, the ROS content increases [49]. In our RNA-seq analysis, we found that PDK1, LDHA, and SLC7A11 were upregulated in MCF7 cells cultured in αMEM. Combined with the results from the KEGG pathway analysis, we speculate that αMEM culture conditions are hypoxic for MCF7 cells. However, the specific reasons for this remain unclear.

Another notable finding of this study is that the mRNA and protein levels of GAPDH were significantly increased in MCF7 cells cultured in αMEM. GAPDH is a housekeeping gene and its expression levels are considered to remain constant in a given cell type. For this reason, it is widely used as a standard internal reference for gene expression analyses such as qPCR and western blotting. GAPDH has pleiotropic effects on cancer progression, invasiveness, and metastasis, and its levels change under specific circumstances [50]. In MCF7 cells, hypoxia increases the expression of GAPDH both at the transcriptional and translational levels [51], which underscores the need for carefully choosing the internal standard for expression studies.

Although we studied the effects of difference culture media on MCF7 cells, we did not conduct in-depth research on the mechanisms. In addition, we only studied the effects of DMEM and αMEM media on MCF7 cells, the role of more culture media types on different cells should be studied.

Conclusions

In this study, we compared the effects of Dulbecco’s modified Eagle medium (DMEM) and minimum essential medium alpha modification (αMEM) on MCF7 cells. The two media differentially affected the morphology, cell cycle, and proliferation of MCF7 cells, but had no effect on cell death. Replacement of DMEM with αMEM led to a decrease in ATP production and an increase in reactive oxygen species production, but did not affect the cell viability.

RNA-sequencing and bioinformatic analyses revealed 721 significantly upregulated and 1247 downregulated genes in cells cultured in αMEM for 48 h compared with that in cells cultured in DMEM. The enriched GO terms were related to mitosis and cell proliferation. The KEGG analysis revealed cell cycle and DNA replication as the top-two significant pathways that were altered in cells cultured in αMEM. These results show that culture medium exerts a considerable effect on cultured cells. Thus, the stability of the culture system is very important to obtain reliable results warranting the need for optimization of the most suitable medium and its consistent use for cell-based studies.

Supporting information

S1 Fig. Correlation analysis between samples.

The X and Y axis represent each sample. The color represents the correlation coefficient (the darker the color, the higher the correlation, the lighter the color, the lower the correlation).

(PDF)

pone.0298262.s001.pdf^{(59.2KB, pdf)}

S2 Fig. PCA analysis.

X axis represents the contributor rate of first component. Y axis represents the contributor rate of second component. Points represent each sample. The samples in one group shows the same color.

(PDF)

pone.0298262.s002.pdf^{(64.9KB, pdf)}

S1 Table. Clean reads quality metrics.

Total Raw Reads(Mb): The reads amount before filtering. Unit: Mb. Total Clean Reads(Mb): The reads amount after filtering. Unit: Mb. Total Clean Bases(Gb): The total base amount after filtering. Unit: Gb. Clean Reads Q20(%): The Q20 value for the clean reads. Clean Reads Q30(%): The Q20 value for the clean reads. Clean Reads Ratio(%): The ratio of the amount of clean reads.

(PDF)

pone.0298262.s003.pdf^{(16.8KB, pdf)}

S1 Raw images

(PDF)

pone.0298262.s004.pdf^{(263KB, pdf)}

Data Availability

The mRNA-seq data from this study has been deposited in the NCBI sequence read archive under the BioProject number PRJNA779251, with the fq files spanning accession numbers SRR16914480-SRR16914481. Direct link to data: https://www.ncbi.nlm.nih.gov/bioproject/PRJNA779251/ The data supporting the research results can also be obtained from the corresponding authors according to reasonable requirements.

Funding Statement

This work was supported by Major Project of Yunnan Science and Technology Program [grant number 202002AA100007 and 202102AA100007-3], Scientific Research Foundation of the Education Department of Yunnan Province [grant number 2021J0226], Joint Special Funds for the Department of Science and Technology of Yunnan Province-Kunming Medical University [grant numbers 2019FE001(-176), 202101AY070001-075]. The amended role of Funder statement are as follows: BR.Z. Grant number 202002AA100007. Major Project of Yunnan Science and Technology Program. Study design. https://kjt.yn.gov.cn BR.Z. Grant number 202102AA100007-3. Major Project of Yunnan Science and Technology Program. Decision to publish. https://kjt.yn.gov.cn BR.Z. Grant number 2021J0226. Scientific Research Foundation of the Education Department of Yunnan Province. Preparation of the manuscript. https://jyt.yn.gov.cn HB.Z. Grant numbers 202101AY070001-075. Joint Special Funds for the Department of Science and Technology of Yunnan Province-Kunming Medical University. Data collection and analysis. https://kjt.yn.gov.cn L.L. Grant numbers 2019FE001(-176). Joint Special Funds for the Department of Science and Technology of Yunnan Province-Kunming Medical University. Data collection and analysis. https://kjt.yn.gov.cn.

References

1.Ferlay J, Colombet M, Soerjomataram I, Mathers C, Parkin DM, Piñeros M, et al. Estimating the global cancer incidence and mortality in 2018: GLOBOCAN sources and methods. Int J Cancer. 2019;144(8):1941–1953. doi: 10.1002/ijc.31937 [DOI] [PubMed] [Google Scholar]
2.Mittal S, Brown NJ, Holen I. The breast tumor microenvironment: role in cancer development, progression and response to therapy. Expert Rev Mol Diagn. 2018;18(3):227–243. doi: 10.1080/14737159.2018.1439382 [DOI] [PubMed] [Google Scholar]
3.Waks AG, Winer EP. Breast Cancer Treatment: A Review. JAMA. 2019;321(3):288–300. doi: 10.1001/jama.2018.19323 [DOI] [PubMed] [Google Scholar]
4.Jafari SH, Saadatpour Z, Salmaninejad A, Momeni F, Mokhtari M, Nahand JS, et al. Breast cancer diagnosis: Imaging techniques and biochemical markers. J Cell Physiol. 2018;233(7):5200–5213. doi: 10.1002/jcp.26379 [DOI] [PubMed] [Google Scholar]
5.Ravi M, Sneka MK, Joshipura A. The culture conditions and outputs from breast cancer cell line in vitro experiments. Exp Cell Res. 2019;383(2):111548. doi: 10.1016/j.yexcr.2019.111548 [DOI] [PubMed] [Google Scholar]
6.Rossi T, Coppi. A, Bruni. E, Ruberto. A, Santachiara. S, Baggio. G. Effects of anti-malarial drugs on MCF-7 and Vero cell replication. Anticancer Res. 2007;27(4B):2555–2559. doi: 10.1016/j.bmcl.2009.07.021 [DOI] [PubMed] [Google Scholar]
7.Johnston H, Dickinson P, Ivens A, Buck AH, Levine RD, Remacle F, et al. Intracellular redox potential is correlated with miRNA expression in MCF7 cells under hypoxic conditions. Proc Natl Acad Sci U S A. 2019;116(39):19753–19759. doi: 10.1073/pnas.1909455116 [DOI] [PMC free article] [PubMed] [Google Scholar]
8.Yang M, Li Y, Shen X, Ruan Y, Lu Y, Jin X, et al. CLDN6 promotes chemoresistance through GSTP1 in human breast cancer. J Exp Clin Cancer Res. 2017;36(1):157. doi: 10.1186/s13046-017-0627-9 [DOI] [PMC free article] [PubMed] [Google Scholar]
9.Brambilla F, Garcia-Manteiga JM, Monteleone E, Hoelzen L, Zocchi A, Agresti A, et al. Nucleosomes effectively shield DNA from radiation damage in living cells. Nucleic Acids Res. 2020;48(16):8993–9006. doi: 10.1093/nar/gkaa613 [DOI] [PMC free article] [PubMed] [Google Scholar]
10.Iturri J, Weber A, Vivanco MD, Toca-Herrera JL. Single-Cell Probe Force Studies to Identify Sox2 Overexpression-Promoted Cell Adhesion in MCF7 Breast Cancer Cells. Cells. 2020;9(4):935. doi: 10.3390/cells9040935 [DOI] [PMC free article] [PubMed] [Google Scholar]
11.Zuo XX, Yang Y, Zhang Y, Zhang ZG, Wang XF, Shi YG. Platelets promote breast cancer cell MCF-7 metastasis by direct interaction: surface integrin α2β1-contacting-mediated activation of Wnt-β-catenin pathway. Cell Commun Signal. 2019;17(1):142. doi: 10.1186/s12964-019-0464-x [DOI] [PMC free article] [PubMed] [Google Scholar]
12.Bahraminasab M, Arab S, Jahan A. Adaptation of MC3T3 cell line to Dulbecco’s Modified Eagle’s medium. Tissue Cell. 2020;64:101341. doi: 10.1016/j.tice.2020.101341 [DOI] [PubMed] [Google Scholar]
13.Pirsko V, Cakstina I, Priedite M, Dortane R, Feldmane L, Nakazawa M, et al. An Effect of Culture Media on Epithelial Differentiation Markers in Breast Cancer Cell Lines MCF7, MDA-MB-436 and SkBr3. Medicina. 2018;30(54):11. doi: 10.3390/medicina54020011 [DOI] [PMC free article] [PubMed] [Google Scholar]
14.Gui DY, Sullivan LB, Luengo A, Hosios AM, Bush LN, Gitego N, et al. Environment Dictates Dependence on Mitochondrial Complex I for NAD+ and Aspartate Production and Determines Cancer Cell Sensitivity to Metformin. Cell Metab. 2016;24(5):716–727. doi: 10.1016/j.cmet.2016.09.006 [DOI] [PMC free article] [PubMed] [Google Scholar]
15.Ackermann T, Tardito S. Cell Culture Medium Formulation and Its Implications in Cancer Metabolism. Trends Cancer. 2019;5(6):329–332. doi: 10.1016/j.trecan.2019.05.004 [DOI] [PMC free article] [PubMed] [Google Scholar]
16.Schubert AK, Smink JJ, Pumberger M, Putzier M, Sittinger M, Ringe J. Standardisation of basal medium for reproducible culture of human annulus fibrosus and nucleus pulposus cells. J Orthop Surg Res. 2018;13(1):209. doi: 10.1186/s13018-018-0914-y [DOI] [PMC free article] [PubMed] [Google Scholar]
17.Chen Y, Chen Y, Shi C, Huang Z, Zhang Y, Li S, et al. SOAPnuke: a MapReduce acceleration-supported software for integrated quality control and preprocessing of high-throughput sequencing data. Gigascience. 2018;7(1):1–6. doi: 10.1093/gigascience/gix120 [DOI] [PMC free article] [PubMed] [Google Scholar]
18.Senthilkumar S, Ulaganathan K, Ghosh DM. Reference-based assembly of chloroplast genome from leaf transcriptome data of Pterocarpus santalinus. 3 Biotech. 2021;11(8):393. doi: 10.1007/s13205-021-02943-0 [DOI] [PMC free article] [PubMed] [Google Scholar]
19.Li B, Dewey CN. RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome. BMC Bioinformatics. 2011;4(12):323. doi: 10.1186/1471-2105-12-323 [DOI] [PMC free article] [PubMed] [Google Scholar]
20.Wang LK, Feng ZX, Wang X, Wang XW, Zhang XG. DEGseq: an R package for identifying differentially expressed genes from RNA-seq data. Bioinformatics. 2010;1(26):136–138. doi: 10.1093/bioinformatics/btp612 [DOI] [PubMed] [Google Scholar]
21.Yu GC, Wang LG, Han YY, He QY. clusterProfiler: an R package for comparing biological themes among gene clusters. OMICS. 2012;16(5). doi: 10.1089/omi.2011.0118 [DOI] [PMC free article] [PubMed] [Google Scholar]
22.Schier AC, Taatjes DJ. Structure and mechanism of the RNA polymerase II transcription machinery. Genes Dev. 2020;34(7–8):465–488. doi: 10.1101/gad.335679.119 [DOI] [PMC free article] [PubMed] [Google Scholar]
23.Franchet C, Hoffmann JS. When RAD52 Allows Mitosis to Accept Unscheduled DNA Synthesis. Cancers (Basel). 2019;12(1):26. doi: 10.3390/cancers12010026 [DOI] [PMC free article] [PubMed] [Google Scholar]
24.Fu J, Glover DM. Structured illumination of the interface between centriole and peri-centriolar material. Open Biol. 2012;2(8):120104. doi: 10.1098/rsob.120104 [DOI] [PMC free article] [PubMed] [Google Scholar]
25.Jamasbi E, Hamelian M, Hossain MA, Varmira K. The cell cycle, cancer development and therapy. Mol Biol Rep. 2022;49(11):10875–10883. doi: 10.1007/s11033-022-07788-1 [DOI] [PubMed] [Google Scholar]
26.Xiong Y, Hannon GJ, Zhang HF, Casso D, Kobayashi R, Beach D. p21 is a universal inhibitor of cyclin kinases. Nature. 1993;366(6456):701–704. doi: 10.1038/366701a0 [DOI] [PubMed] [Google Scholar]
27.Tian Y, Wan H, Tan G. Cell cycle-related kinase in carcinogenesis. Oncol Lett. 2012;4(4):601–606. doi: 10.3892/ol.2012.828 [DOI] [PMC free article] [PubMed] [Google Scholar]
28.Kreis NN, Louwen F, Yuan J. The Multifaceted p21 (Cip1/Waf1/CDKN1A) in Cell Differentiation, Migration and Cancer Therapy. Cancers (Basel). 2019;11(9):1220. doi: 10.3390/cancers11091220 [DOI] [PMC free article] [PubMed] [Google Scholar]
29.Sheng C, Mendler IH, Rieke S, Snyder P, Jentsch M, Friedrich D, et al. PCNA-Mediated Degradation of p21 Coordinates the DNA Damage Response and Cell Cycle Regulation in Individual Cells. Cell Rep. 2019;27(1):48–58. doi: 10.1016/j.celrep.2019.03.031 [DOI] [PubMed] [Google Scholar]
30.Kreis NN, Friemel A, Zimmer B, Roth S, Rieger MA, Rolle U, et al. Mitotic p21Cip1/CDKN1A is regulated by cyclin-dependent kinase 1 phosphorylation. Oncotarget. 2016;7(31):50215–50228. doi: 10.18632/oncotarget.10330 [DOI] [PMC free article] [PubMed] [Google Scholar]
31.Barboza JA, Liu G, Ju Z, El-Naggar AK, Lozano G. p21 delays tumor onset by preservation of chromosomal stability. Proc Natl Acad Sci U S A. 2006;103(52):19842–19847. doi: 10.1073/pnas.0606343104 [DOI] [PMC free article] [PubMed] [Google Scholar]
32.Hsu CH, Altschuler SJ, Wu LF. Patterns of Early p21 Dynamics Determine Proliferation-Senescence Cell Fate after Chemotherapy. Cell. 2019;178(2):361–373. doi: 10.1016/j.cell.2019.05.041 [DOI] [PMC free article] [PubMed] [Google Scholar]
33.Malumbres M. Cyclin-dependent kinases. Genome Biol. 2014;15(6):122. doi: 10.1186/gb4184 [DOI] [PMC free article] [PubMed] [Google Scholar]
34.Prevo R, Pirovano G, Puliyadi R, Herbert KJ, Rodriguez-Berriguete G, O’Docherty A, et al. CDK1 inhibition sensitizes normal cells to DNA damage in a cell cycle dependent manner. Cell Cycle. 2018;17(12):1513–1523. doi: 10.1080/15384101.2018.1491236 [DOI] [PMC free article] [PubMed] [Google Scholar]
35.Castro IPD, Cárcer GD, Marcos M. A census of mitotic cancer genes: new insights into tumor cell biology and cancer therapy. Carcinogenesis. 2007;28(5):899–912. doi: 10.1093/carcin/bgm019 [DOI] [PubMed] [Google Scholar]
36.Haneke K, Schott J, Lindner D, Hollensen AK, Damgaard CK, Mongis C, et al. CDK1 couples proliferation with protein synthesis. J Cell Biol. 2020;219(3):e201906147. doi: 10.1083/jcb.201906147 [DOI] [PMC free article] [PubMed] [Google Scholar]
37.Bashir TF, Pagano M. Cdk1: the dominant sibling of Cdk2. Nat Cell Biol. 2005;7(8):779–781. doi: 10.1038/ncb0805-779 [DOI] [PubMed] [Google Scholar]
38.Xie B, Wang S, Jiang N, Li JJ. Cyclin B1/CDK1-regulated mitochondrial bioenergetics in cell cycle progression and tumor resistance. Cancer Lett. 2019;443:56–66. doi: 10.1016/j.canlet.2018.11.019 [DOI] [PMC free article] [PubMed] [Google Scholar]
39.Jones MC, Askari JA, Humphries JD, Humphries MJ. Cell adhesion is regulated by CDK1 during the cell cycle. J Cell Biol. 2018;217(9):3203–3218. doi: 10.1083/jcb.201802088 [DOI] [PMC free article] [PubMed] [Google Scholar]
40.Iyer NV, Kotch LE, Agani F, Leung SW, Laughner E, Wenger RH, et al. Cellular and developmental control of O₂ homeostasis by hypoxia-inducible factor 1 alpha. Genes Dev. 1998;12(2):149–162. doi: 10.1101/gad.12.2.149 [DOI] [PMC free article] [PubMed] [Google Scholar]
41.Heer ECD, Jalving M, Harris AL. HIFs, angiogenesis, and metabolism: elusive enemies in breast cancer. J Clin Invest. 2020;130(10):5074–5087. doi: 10.1172/JCI137552 [DOI] [PMC free article] [PubMed] [Google Scholar]
42.Semenza GL. Hypoxia-inducible factors: coupling glucose metabolism and redox regulation with induction of the breast cancer stem cell phenotype. EMBO J. 2017;36(3):252–259. doi: 10.15252/embj.201695204 [DOI] [PMC free article] [PubMed] [Google Scholar]
43.Huang CS, Chang LS, Anderson ME, Meister A. Catalytic and regulatory properties of the heavy subunit of rat kidney gamma-glutamylcysteine synthetase. J Biol Chem. 1993;268(26):19675–19680. doi: 10.1016/S0021-9258(19)36569-X [DOI] [PubMed] [Google Scholar]
44.Lane N, Martin W. The energetics of genome complexity. Nature. 2010;467(7318):929–934. doi: 10.1038/nature09486 [DOI] [PubMed] [Google Scholar]
45.Rai G, Brimacombe KR, Mott BT, Urban DJ, Hu X, Yang SM, et al. Discovery and Optimization of Potent, Cell-Active Pyrazole-Based Inhibitors of Lactate Dehydrogenase (LDH). J Med Chem. 2017;60(22):9184–9204. doi: 10.1021/acs.jmedchem.7b00941 [DOI] [PMC free article] [PubMed] [Google Scholar]
46.Papandreou I, Cairns RA, Fontana L, Lim AL, Denko NC. HIF-1 mediates adaptation to hypoxia by actively downregulating mitochondrial oxygen consumption. Cell Metab. 2006;3(3):187–197. doi: 10.1016/j.cmet.2006.01.012 [DOI] [PubMed] [Google Scholar]
47.Kim JW, Tchernyshyov I, Semenza GL, Dang CV. HIF-1-mediated expression of pyruvate dehydrogenase kinase: a metabolic switch required for cellular adaptation to hypoxia. Cell Metab. 2006;3(3):177–185. doi: 10.1016/j.cmet.2006.02.002 [DOI] [PubMed] [Google Scholar]
48.Lu H, Samanta D, Xiang L, Zhang H, Hu H, Chen I, et al. Chemotherapy triggers HIF-1-dependent glutathione synthesis and copper chelation that induces the breast cancer stem cell phenotype. Proc Natl Acad Sci U S A. 2015;112(33):E4600–4609. doi: 10.1073/pnas.1513433112 [DOI] [PMC free article] [PubMed] [Google Scholar]
49.Okoye CN, Koren SA, Wojtovich AP. Mitochondrial complex I ROS production and redox signaling in hypoxia. Redox Biol. 2023;67:102926. doi: 10.1016/j.redox.2023.102926 [DOI] [PMC free article] [PubMed] [Google Scholar]
50.Sirover MA. Pleiotropic effects of moonlighting glyceraldehyde-3-phosphate dehydrogenase (GAPDH) in cancer progression, invasiveness, and metastases. Cancer Metastasis Rev. 2018;37(4):665–676. doi: 10.1007/s10555-018-9764-7 [DOI] [PubMed] [Google Scholar]
51.Higashimura Y, Nakajima Y, Yamaji R, Harada N, Shibasaki F, Nakano Y, et al. Up-regulation of glyceraldehyde-3-phosphate dehydrogenase gene expression by HIF-1 activity depending on Sp1 in hypoxic breast cancer cells. Arch Biochem Biophys. 2011;509(1):1–8. doi: 10.1016/j.abb.2011.02.011 [DOI] [PubMed] [Google Scholar]

PLoS One. doi: 10.1371/journal.pone.0298262.r001

Decision Letter 0

Sadiq Umar

22 Nov 2023

PONE-D-23-29345Transcriptome-wide analysis of the difference between MCF7 cells cultured in DMEM or αMEMPLOS ONE

Dear Dr. Zheng,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

Please submit your revised manuscript by Jan 05 2024 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.
A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.
An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: https://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols. Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols.

We look forward to receiving your revised manuscript.

Kind regards,

Sadiq Umar

Academic Editor

PLOS ONE

Journal Requirements:

When submitting your revision, we need you to address these additional requirements.

1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at

https://journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf and

https://journals.plos.org/plosone/s/file?id=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdf

2. We noticed you have some minor occurrence of overlapping text with the following previous publication(s), which needs to be addressed:

https://www.hindawi.com/journals/sci/2018/5912194/

In your revision ensure you cite all your sources (including your own works), and quote or rephrase any duplicated text outside the methods section. Further consideration is dependent on these concerns being addressed.

3. Note from Emily Chenette, Editor in Chief of PLOS ONE, and Iain Hrynaszkiewicz, Director of Open Research Solutions at PLOS: Did you know that depositing data in a repository is associated with up to a 25% citation advantage (https://doi.org/10.1371/journal.pone.0230416)? If you’ve not already done so, consider depositing your raw data in a repository to ensure your work is read, appreciated and cited by the largest possible audience. You’ll also earn an Accessible Data icon on your published paper if you deposit your data in any participating repository (https://plos.org/open-science/open-data/#accessible-data).

4. We note that the grant information you provided in the ‘Funding Information’ and ‘Financial Disclosure’ sections do not match.

When you resubmit, please ensure that you provide the correct grant numbers for the awards you received for your study in the ‘Funding Information’ section.

5. Thank you for stating the following financial disclosure:

"This work was supported by Major Project of Yunnan Science and Technology Program [grant number 202002AA100007 and 202102AA100007-3], Scientific Research Foundation of the Education Department of Yunnan Province [grant number 2021J0226], Joint Special Funds for the Department of Science and Technology of Yunnan Province-Kunming Medical University [grant numbers 2019FE001(-176), 202101AY070001-075]."

Please state what role the funders took in the study. If the funders had no role, please state: "The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript."

If this statement is not correct you must amend it as needed.

Please include this amended Role of Funder statement in your cover letter; we will change the online submission form on your behalf.

6. Thank you for stating the following in your Competing Interests section:

'The authors declare no conflicts of interest."

Please complete your Competing Interests on the online submission form to state any Competing Interests. If you have no competing interests, please state "The authors have declared that no competing interests exist.", as detailed online in our guide for authors at http://journals.plos.org/plosone/s/submit-now

This information should be included in your cover letter; we will change the online submission form on your behalf.

7. PLOS ONE now requires that authors provide the original uncropped and unadjusted images underlying all blot or gel results reported in a submission’s figures or Supporting Information files. This policy and the journal’s other requirements for blot/gel reporting and figure preparation are described in detail at https://journals.plos.org/plosone/s/figures#loc-blot-and-gel-reporting-requirements and https://journals.plos.org/plosone/s/figures#loc-preparing-figures-from-image-files. When you submit your revised manuscript, please ensure that your figures adhere fully to these guidelines and provide the original underlying images for all blot or gel data reported in your submission. See the following link for instructions on providing the original image data: https://journals.plos.org/plosone/s/figures#loc-original-images-for-blots-and-gels.

In your cover letter, please note whether your blot/gel image data are in Supporting Information or posted at a public data repository, provide the repository URL if relevant, and provide specific details as to which raw blot/gel images, if any, are not available. Email us at plosone@plos.org if you have any questions.

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: No

Reviewer #2: Yes

**********

2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: No

Reviewer #2: Yes

**********

3. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: No

Reviewer #2: Yes

**********

4. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: No

Reviewer #2: Yes

**********

5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: The manuscript entitled “Transcriptome-wide analysis of the difference between MCF7 cells 2 cultured in DMEM or αMEM” aims to demonstrate the effect of culture medium on MCF7 cells in terms of transcriptomic profiling. The manuscript is poorly written and lack the significance and novelty of the study. My comments are as follows.

1. What is the rationale of this study? Cells grown in different culture media will definitely give different phenotype. Every cell culture has its definite and defined media to culture and proceed the analysis.

2. Pease provide the details of RNA sequencing, like library preparation and sequencing. Please provide PCA for the QC of RNA sequencing.

3. English mistakes are prevalent throughout the manuscript. Please rectify.

4. Missing legends of the figures. Hard to assess the figures and correlate with the results.

5. The manuscript lacks mechanism.

Reviewer #2: Title: Transcriptome-wide analysis of the difference between MCF7 cells cultured in DMEM or αMEM

Reviewer’s report

The authors have examined the effect of two different types of cell culture media on breast cancer model 'MCF7'. Based on RNA sequencing data they found that culturing the MCF7 cells in different culture media led to differential gene expression. Moreover, they found that cells that were cultured in alpha-MEM were hypoxic. This study reveals that culture media plays an important role on cell growth property at morphological, biological and transcriptional level, thus it is utmost important to choose the correct cell culture media for a specific cell type to obtain reliable results. The present study reveals interesting findings; however, there are several essential points that need to be addressed before publication.

Minor Comments:

1) In Introduction line no 75, authors have mentioned about NP cells without its introduction. Please explain a little bit more about NP cells and its significance here in this current study.

2) It would be interesting if authors could also show the effect of different culture media on cell growth and proliferation by colony forming assay.

3) In all the results (graphs) please include individual data points that would give a clear indication about number of replicates in each group.

4) What was the effect of different cultures media on cell attachment to the surface of the cell culture flasks. Were there any differences observed by authors in terms of cell attachment.

5) Did authors find any differential effect of culturing MCF7 in Mitochondrial respiration and intracellular ATP levels or morphological changes at organelle level?

6) It would be interesting to look at the effect of culturing MCF7 in different culture media on the expression of MCF7 specific genes like Insulin like growth factor binding protein 2, WNT7B and LHR expression?

**********

6. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

Reviewer #2: No

**********

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.]

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step.

PLoS One. 2024 Mar 28;19(3):e0298262. doi: 10.1371/journal.pone.0298262.r002

Author response to Decision Letter 0

21 Jan 2024

Dear Editor,

Thank you for giving us the opportunity to revise our manuscript entitled “Transcriptome-wide analysis of the difference between MCF7 cells cultured in DMEM or αMEM (Manuscript ID: PONE-D-23-29345)". Sorry for the late submission. We now have completed our revision. The responds to the reviewer’s comments are as flowing:

1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at

https://journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf and https://journals.plos.org/plosone/s/file?id=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdf

We have revised the format of our article according to PLOS ONE's style requirements, including file naming.

2. We noticed you have some minor occurrence of overlapping text with the following previous publication(s), which needs to be addressed: https://www.hindawi.com/journals/sci/2018/5912194/

We have quoted or rephrased the duplicated text outside the methods section.

The mRNA-seq data from this study has been deposited in the NCBI sequence read archive under the BioProject number PRJNA779251, with the fq files spanning accession numbers SRR16914480-SRR16914481.

4. We note that the grant information you provided in the ‘Funding Information’ and ‘Financial Disclosure’ sections do not match.

When you resubmit, please ensure that you provide the correct grant numbers for the awards you received for your study in the ‘Funding Information’ section.

We have corrected the ‘Funding Information’ according to the ‘Financial Disclosure’ sections, and we ensure that the grant numbers are correct.

5. Thank you for stating the following financial disclosure:

If this statement is not correct you must amend it as needed.

Please include this amended Role of Funder statement in your cover letter; we will change the online submission form on your behalf.

We have corrected the ‘Funding Information’ according to the ‘Financial Disclosure’ sections, and we ensure that the grant numbers are correct, and we have added it in the cover letter.

6. Thank you for stating the following in your Competing Interests section:

'The authors declare no conflicts of interest."

This information should be included in your cover letter; we will change the online submission form on your behalf.

We have completed our Competing Interests on the online submission form and cover letter.

We have uploaded the original uncropped and unadjusted images underlying all blot results reported in a submission’s figures as “S1_raw_images”.

Response to Reviewer 1

Thank you for your careful reading and giving us useful suggestions.

The manuscript entitled “Transcriptome-wide analysis of the difference between MCF7 cells 2 cultured in DMEM or αMEM” aims to demonstrate the effect of culture medium on MCF7 cells in terms of transcriptomic profiling. The manuscript is poorly written and lack the significance and novelty of the study.

We have supplemented the experiments based on the comments from reviewers and made revisions to our manuscript to highlight the key points. We hope this manuscript is appropriate for publication.

Although it is well known that different culture media can cause different phenotypes in cells, we do not yet know in which specific aspects they impact on, especially on the cellular genome. Also, few people would spend time and experience doing this study. Therefore, our research can provide a reference.

2. Pease provide the details of RNA sequencing, like library preparation and sequencing. Please provide PCA for the QC of RNA sequencing.

We have added these contents to “RNA isolation and RNA-Seq library preparation” and “Differential gene expression and gene enrichment analysis” of “Materials and Methods” in manuscript.

3. English mistakes are prevalent throughout the manuscript. Please rectify.

Thank you for your reminder, and we have rectified these mistakes.

4. Missing legends of the figures. Hard to assess the figures and correlate with the results.

We have added the legends of the figures.

5. The manuscript lacks mechanism.

We will further study the mechanism in the future.

Response to Reviewer 2

Thank you for your careful reading and giving us useful suggestions.

Minor Comments:

1) In Introduction line no 75, authors have mentioned about NP cells without its introduction. Please explain a little bit more about NP cells and its significance here in this current study.

Thank you for your reminder. We have carefully read the context and found that NP cells are indeed abrupt and unimportant here in this current study, so we have deleted this sentence.

2) It would be interesting if authors could also show the effect of different culture media on cell growth and proliferation by colony forming assay.

We have performed cell colony forming experiments and included the results in the manuscript.

3) In all the results (graphs) please include individual data points that would give a clear indication about number of replicates in each group.

We have remade the graphs to include individual data points.

4) What was the effect of different cultures media on cell attachment to the surface of the cell culture flasks. Were there any differences observed by authors in terms of cell attachment.

We have performed cell attachment experiments and included the results in the manuscript.

5) Did authors find any differential effect of culturing MCF7 in Mitochondrial respiration and intracellular ATP levels or morphological changes at organelle level?

We have detected the intracellular ATP levels and included the results in the manuscript.

We conducted t-tests on the expression values (FPKM) of three genes. The results were that the p-value of the Insulin like growth factor binding protein 2 gene was 0.01977, which was slightly higher in C1, and the p-value of WNT7B and LHR were 0.05227 and 0.9694, which were no significant difference.

Attachment

Submitted filename: Response to Reviewers.docx

pone.0298262.s005.docx^{(23.4KB, docx)}

PLoS One. doi: 10.1371/journal.pone.0298262.r003

Decision Letter 1

Sadiq Umar

23 Jan 2024

Transcriptome-wide analysis of the difference between MCF7 cells cultured in DMEM or αMEM

PONE-D-23-29345R1

Dear Dr. Zheng,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

An invoice for payment will follow shortly after the formal acceptance. To ensure an efficient process, please log into Editorial Manager at http://www.editorialmanager.com/pone/, click the 'Update My Information' link at the top of the page, and double check that your user information is up-to-date. If you have any billing related questions, please contact our Author Billing department directly at authorbilling@plos.org.

If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org.

Kind regards,

Sadiq Umar

Academic Editor

PLOS ONE

PLoS One. doi: 10.1371/journal.pone.0298262.r004

Acceptance letter

Sadiq Umar

20 Mar 2024

PONE-D-23-29345R1

PLOS ONE

Dear Dr. Zheng,

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now being handed over to our production team.

At this stage, our production department will prepare your paper for publication. This includes ensuring the following:

* All references, tables, and figures are properly cited

* All relevant supporting information is included in the manuscript submission,

* There are no issues that prevent the paper from being properly typeset

If revisions are needed, the production department will contact you directly to resolve them. If no revisions are needed, you will receive an email when the publication date has been set. At this time, we do not offer pre-publication proofs to authors during production of the accepted work. Please keep in mind that we are working through a large volume of accepted articles, so please give us a few weeks to review your paper and let you know the next and final steps.

Lastly, if your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org.

If we can help with anything else, please email us at customercare@plos.org.

Thank you for submitting your work to PLOS ONE and supporting open access.

Kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Dr. Sadiq Umar

Academic Editor

PLOS ONE

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

S1 Fig. Correlation analysis between samples.

The X and Y axis represent each sample. The color represents the correlation coefficient (the darker the color, the higher the correlation, the lighter the color, the lower the correlation).

(PDF)

pone.0298262.s001.pdf^{(59.2KB, pdf)}

S2 Fig. PCA analysis.

X axis represents the contributor rate of first component. Y axis represents the contributor rate of second component. Points represent each sample. The samples in one group shows the same color.

(PDF)

pone.0298262.s002.pdf^{(64.9KB, pdf)}

S1 Table. Clean reads quality metrics.

(PDF)

pone.0298262.s003.pdf^{(16.8KB, pdf)}

S1 Raw images

(PDF)

pone.0298262.s004.pdf^{(263KB, pdf)}

Attachment

Submitted filename: Response to Reviewers.docx

pone.0298262.s005.docx^{(23.4KB, docx)}

Data Availability Statement

[pone.0298262.ref001] 1.Ferlay J, Colombet M, Soerjomataram I, Mathers C, Parkin DM, Piñeros M, et al. Estimating the global cancer incidence and mortality in 2018: GLOBOCAN sources and methods. Int J Cancer. 2019;144(8):1941–1953. doi: 10.1002/ijc.31937 [DOI] [PubMed] [Google Scholar]

[pone.0298262.ref002] 2.Mittal S, Brown NJ, Holen I. The breast tumor microenvironment: role in cancer development, progression and response to therapy. Expert Rev Mol Diagn. 2018;18(3):227–243. doi: 10.1080/14737159.2018.1439382 [DOI] [PubMed] [Google Scholar]

[pone.0298262.ref003] 3.Waks AG, Winer EP. Breast Cancer Treatment: A Review. JAMA. 2019;321(3):288–300. doi: 10.1001/jama.2018.19323 [DOI] [PubMed] [Google Scholar]

[pone.0298262.ref004] 4.Jafari SH, Saadatpour Z, Salmaninejad A, Momeni F, Mokhtari M, Nahand JS, et al. Breast cancer diagnosis: Imaging techniques and biochemical markers. J Cell Physiol. 2018;233(7):5200–5213. doi: 10.1002/jcp.26379 [DOI] [PubMed] [Google Scholar]

[pone.0298262.ref005] 5.Ravi M, Sneka MK, Joshipura A. The culture conditions and outputs from breast cancer cell line in vitro experiments. Exp Cell Res. 2019;383(2):111548. doi: 10.1016/j.yexcr.2019.111548 [DOI] [PubMed] [Google Scholar]

[pone.0298262.ref006] 6.Rossi T, Coppi. A, Bruni. E, Ruberto. A, Santachiara. S, Baggio. G. Effects of anti-malarial drugs on MCF-7 and Vero cell replication. Anticancer Res. 2007;27(4B):2555–2559. doi: 10.1016/j.bmcl.2009.07.021 [DOI] [PubMed] [Google Scholar]

[pone.0298262.ref007] 7.Johnston H, Dickinson P, Ivens A, Buck AH, Levine RD, Remacle F, et al. Intracellular redox potential is correlated with miRNA expression in MCF7 cells under hypoxic conditions. Proc Natl Acad Sci U S A. 2019;116(39):19753–19759. doi: 10.1073/pnas.1909455116 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0298262.ref008] 8.Yang M, Li Y, Shen X, Ruan Y, Lu Y, Jin X, et al. CLDN6 promotes chemoresistance through GSTP1 in human breast cancer. J Exp Clin Cancer Res. 2017;36(1):157. doi: 10.1186/s13046-017-0627-9 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0298262.ref009] 9.Brambilla F, Garcia-Manteiga JM, Monteleone E, Hoelzen L, Zocchi A, Agresti A, et al. Nucleosomes effectively shield DNA from radiation damage in living cells. Nucleic Acids Res. 2020;48(16):8993–9006. doi: 10.1093/nar/gkaa613 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0298262.ref010] 10.Iturri J, Weber A, Vivanco MD, Toca-Herrera JL. Single-Cell Probe Force Studies to Identify Sox2 Overexpression-Promoted Cell Adhesion in MCF7 Breast Cancer Cells. Cells. 2020;9(4):935. doi: 10.3390/cells9040935 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0298262.ref011] 11.Zuo XX, Yang Y, Zhang Y, Zhang ZG, Wang XF, Shi YG. Platelets promote breast cancer cell MCF-7 metastasis by direct interaction: surface integrin α2β1-contacting-mediated activation of Wnt-β-catenin pathway. Cell Commun Signal. 2019;17(1):142. doi: 10.1186/s12964-019-0464-x [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0298262.ref012] 12.Bahraminasab M, Arab S, Jahan A. Adaptation of MC3T3 cell line to Dulbecco’s Modified Eagle’s medium. Tissue Cell. 2020;64:101341. doi: 10.1016/j.tice.2020.101341 [DOI] [PubMed] [Google Scholar]

[pone.0298262.ref013] 13.Pirsko V, Cakstina I, Priedite M, Dortane R, Feldmane L, Nakazawa M, et al. An Effect of Culture Media on Epithelial Differentiation Markers in Breast Cancer Cell Lines MCF7, MDA-MB-436 and SkBr3. Medicina. 2018;30(54):11. doi: 10.3390/medicina54020011 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0298262.ref014] 14.Gui DY, Sullivan LB, Luengo A, Hosios AM, Bush LN, Gitego N, et al. Environment Dictates Dependence on Mitochondrial Complex I for NAD+ and Aspartate Production and Determines Cancer Cell Sensitivity to Metformin. Cell Metab. 2016;24(5):716–727. doi: 10.1016/j.cmet.2016.09.006 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0298262.ref015] 15.Ackermann T, Tardito S. Cell Culture Medium Formulation and Its Implications in Cancer Metabolism. Trends Cancer. 2019;5(6):329–332. doi: 10.1016/j.trecan.2019.05.004 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0298262.ref016] 16.Schubert AK, Smink JJ, Pumberger M, Putzier M, Sittinger M, Ringe J. Standardisation of basal medium for reproducible culture of human annulus fibrosus and nucleus pulposus cells. J Orthop Surg Res. 2018;13(1):209. doi: 10.1186/s13018-018-0914-y [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0298262.ref017] 17.Chen Y, Chen Y, Shi C, Huang Z, Zhang Y, Li S, et al. SOAPnuke: a MapReduce acceleration-supported software for integrated quality control and preprocessing of high-throughput sequencing data. Gigascience. 2018;7(1):1–6. doi: 10.1093/gigascience/gix120 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0298262.ref018] 18.Senthilkumar S, Ulaganathan K, Ghosh DM. Reference-based assembly of chloroplast genome from leaf transcriptome data of Pterocarpus santalinus. 3 Biotech. 2021;11(8):393. doi: 10.1007/s13205-021-02943-0 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0298262.ref019] 19.Li B, Dewey CN. RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome. BMC Bioinformatics. 2011;4(12):323. doi: 10.1186/1471-2105-12-323 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0298262.ref020] 20.Wang LK, Feng ZX, Wang X, Wang XW, Zhang XG. DEGseq: an R package for identifying differentially expressed genes from RNA-seq data. Bioinformatics. 2010;1(26):136–138. doi: 10.1093/bioinformatics/btp612 [DOI] [PubMed] [Google Scholar]

[pone.0298262.ref021] 21.Yu GC, Wang LG, Han YY, He QY. clusterProfiler: an R package for comparing biological themes among gene clusters. OMICS. 2012;16(5). doi: 10.1089/omi.2011.0118 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0298262.ref022] 22.Schier AC, Taatjes DJ. Structure and mechanism of the RNA polymerase II transcription machinery. Genes Dev. 2020;34(7–8):465–488. doi: 10.1101/gad.335679.119 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0298262.ref023] 23.Franchet C, Hoffmann JS. When RAD52 Allows Mitosis to Accept Unscheduled DNA Synthesis. Cancers (Basel). 2019;12(1):26. doi: 10.3390/cancers12010026 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0298262.ref024] 24.Fu J, Glover DM. Structured illumination of the interface between centriole and peri-centriolar material. Open Biol. 2012;2(8):120104. doi: 10.1098/rsob.120104 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0298262.ref025] 25.Jamasbi E, Hamelian M, Hossain MA, Varmira K. The cell cycle, cancer development and therapy. Mol Biol Rep. 2022;49(11):10875–10883. doi: 10.1007/s11033-022-07788-1 [DOI] [PubMed] [Google Scholar]

[pone.0298262.ref026] 26.Xiong Y, Hannon GJ, Zhang HF, Casso D, Kobayashi R, Beach D. p21 is a universal inhibitor of cyclin kinases. Nature. 1993;366(6456):701–704. doi: 10.1038/366701a0 [DOI] [PubMed] [Google Scholar]

[pone.0298262.ref027] 27.Tian Y, Wan H, Tan G. Cell cycle-related kinase in carcinogenesis. Oncol Lett. 2012;4(4):601–606. doi: 10.3892/ol.2012.828 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0298262.ref028] 28.Kreis NN, Louwen F, Yuan J. The Multifaceted p21 (Cip1/Waf1/CDKN1A) in Cell Differentiation, Migration and Cancer Therapy. Cancers (Basel). 2019;11(9):1220. doi: 10.3390/cancers11091220 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0298262.ref029] 29.Sheng C, Mendler IH, Rieke S, Snyder P, Jentsch M, Friedrich D, et al. PCNA-Mediated Degradation of p21 Coordinates the DNA Damage Response and Cell Cycle Regulation in Individual Cells. Cell Rep. 2019;27(1):48–58. doi: 10.1016/j.celrep.2019.03.031 [DOI] [PubMed] [Google Scholar]

[pone.0298262.ref030] 30.Kreis NN, Friemel A, Zimmer B, Roth S, Rieger MA, Rolle U, et al. Mitotic p21Cip1/CDKN1A is regulated by cyclin-dependent kinase 1 phosphorylation. Oncotarget. 2016;7(31):50215–50228. doi: 10.18632/oncotarget.10330 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0298262.ref031] 31.Barboza JA, Liu G, Ju Z, El-Naggar AK, Lozano G. p21 delays tumor onset by preservation of chromosomal stability. Proc Natl Acad Sci U S A. 2006;103(52):19842–19847. doi: 10.1073/pnas.0606343104 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0298262.ref032] 32.Hsu CH, Altschuler SJ, Wu LF. Patterns of Early p21 Dynamics Determine Proliferation-Senescence Cell Fate after Chemotherapy. Cell. 2019;178(2):361–373. doi: 10.1016/j.cell.2019.05.041 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0298262.ref033] 33.Malumbres M. Cyclin-dependent kinases. Genome Biol. 2014;15(6):122. doi: 10.1186/gb4184 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0298262.ref034] 34.Prevo R, Pirovano G, Puliyadi R, Herbert KJ, Rodriguez-Berriguete G, O’Docherty A, et al. CDK1 inhibition sensitizes normal cells to DNA damage in a cell cycle dependent manner. Cell Cycle. 2018;17(12):1513–1523. doi: 10.1080/15384101.2018.1491236 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0298262.ref035] 35.Castro IPD, Cárcer GD, Marcos M. A census of mitotic cancer genes: new insights into tumor cell biology and cancer therapy. Carcinogenesis. 2007;28(5):899–912. doi: 10.1093/carcin/bgm019 [DOI] [PubMed] [Google Scholar]

[pone.0298262.ref036] 36.Haneke K, Schott J, Lindner D, Hollensen AK, Damgaard CK, Mongis C, et al. CDK1 couples proliferation with protein synthesis. J Cell Biol. 2020;219(3):e201906147. doi: 10.1083/jcb.201906147 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0298262.ref037] 37.Bashir TF, Pagano M. Cdk1: the dominant sibling of Cdk2. Nat Cell Biol. 2005;7(8):779–781. doi: 10.1038/ncb0805-779 [DOI] [PubMed] [Google Scholar]

[pone.0298262.ref038] 38.Xie B, Wang S, Jiang N, Li JJ. Cyclin B1/CDK1-regulated mitochondrial bioenergetics in cell cycle progression and tumor resistance. Cancer Lett. 2019;443:56–66. doi: 10.1016/j.canlet.2018.11.019 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0298262.ref039] 39.Jones MC, Askari JA, Humphries JD, Humphries MJ. Cell adhesion is regulated by CDK1 during the cell cycle. J Cell Biol. 2018;217(9):3203–3218. doi: 10.1083/jcb.201802088 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0298262.ref040] 40.Iyer NV, Kotch LE, Agani F, Leung SW, Laughner E, Wenger RH, et al. Cellular and developmental control of O₂ homeostasis by hypoxia-inducible factor 1 alpha. Genes Dev. 1998;12(2):149–162. doi: 10.1101/gad.12.2.149 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0298262.ref041] 41.Heer ECD, Jalving M, Harris AL. HIFs, angiogenesis, and metabolism: elusive enemies in breast cancer. J Clin Invest. 2020;130(10):5074–5087. doi: 10.1172/JCI137552 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0298262.ref042] 42.Semenza GL. Hypoxia-inducible factors: coupling glucose metabolism and redox regulation with induction of the breast cancer stem cell phenotype. EMBO J. 2017;36(3):252–259. doi: 10.15252/embj.201695204 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0298262.ref043] 43.Huang CS, Chang LS, Anderson ME, Meister A. Catalytic and regulatory properties of the heavy subunit of rat kidney gamma-glutamylcysteine synthetase. J Biol Chem. 1993;268(26):19675–19680. doi: 10.1016/S0021-9258(19)36569-X [DOI] [PubMed] [Google Scholar]

[pone.0298262.ref044] 44.Lane N, Martin W. The energetics of genome complexity. Nature. 2010;467(7318):929–934. doi: 10.1038/nature09486 [DOI] [PubMed] [Google Scholar]

[pone.0298262.ref045] 45.Rai G, Brimacombe KR, Mott BT, Urban DJ, Hu X, Yang SM, et al. Discovery and Optimization of Potent, Cell-Active Pyrazole-Based Inhibitors of Lactate Dehydrogenase (LDH). J Med Chem. 2017;60(22):9184–9204. doi: 10.1021/acs.jmedchem.7b00941 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0298262.ref046] 46.Papandreou I, Cairns RA, Fontana L, Lim AL, Denko NC. HIF-1 mediates adaptation to hypoxia by actively downregulating mitochondrial oxygen consumption. Cell Metab. 2006;3(3):187–197. doi: 10.1016/j.cmet.2006.01.012 [DOI] [PubMed] [Google Scholar]

[pone.0298262.ref047] 47.Kim JW, Tchernyshyov I, Semenza GL, Dang CV. HIF-1-mediated expression of pyruvate dehydrogenase kinase: a metabolic switch required for cellular adaptation to hypoxia. Cell Metab. 2006;3(3):177–185. doi: 10.1016/j.cmet.2006.02.002 [DOI] [PubMed] [Google Scholar]

[pone.0298262.ref048] 48.Lu H, Samanta D, Xiang L, Zhang H, Hu H, Chen I, et al. Chemotherapy triggers HIF-1-dependent glutathione synthesis and copper chelation that induces the breast cancer stem cell phenotype. Proc Natl Acad Sci U S A. 2015;112(33):E4600–4609. doi: 10.1073/pnas.1513433112 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0298262.ref049] 49.Okoye CN, Koren SA, Wojtovich AP. Mitochondrial complex I ROS production and redox signaling in hypoxia. Redox Biol. 2023;67:102926. doi: 10.1016/j.redox.2023.102926 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0298262.ref050] 50.Sirover MA. Pleiotropic effects of moonlighting glyceraldehyde-3-phosphate dehydrogenase (GAPDH) in cancer progression, invasiveness, and metastases. Cancer Metastasis Rev. 2018;37(4):665–676. doi: 10.1007/s10555-018-9764-7 [DOI] [PubMed] [Google Scholar]

[pone.0298262.ref051] 51.Higashimura Y, Nakajima Y, Yamaji R, Harada N, Shibasaki F, Nakano Y, et al. Up-regulation of glyceraldehyde-3-phosphate dehydrogenase gene expression by HIF-1 activity depending on Sp1 in hypoxic breast cancer cells. Arch Biochem Biophys. 2011;509(1):1–8. doi: 10.1016/j.abb.2011.02.011 [DOI] [PubMed] [Google Scholar]

PERMALINK

Transcriptome-wide analysis of the differences between MCF7 cells cultured in DMEM or αMEM

Yang Jiao

Hongbo Zhao

Lin Lu

Xiangyu Zhao

Yanchun Wang

Bingrong Zheng

Roles

Abstract

Introduction

Materials and methods

Cell culture

Exposure of MCF7 cells to a different medium

Flow cytometric analysis of the cell cycle

Annexin V-FITC/PI staining

Cell attachment assay

Colony formation assay

ATP detection

ROS and cell proliferation assays

RNA isolation and RNA-Seq library preparation

Differential gene expression and gene enrichment analysis

Validation of sequencing-based gene expression levels via quantitative real-time polymerase chain reactions (qPCR)

Table 1. Sequences of the primers used in the quantitative real-time polymerase chain reactions.

Western blot analysis

Statistical analyses

Results

Effect of culture medium on cell cycle and proliferation

Fig 1. Cell morphology.

Fig 2. Cell cycle analysis.

Fig 3. Flow cytometry results of Annexin V-FITC/PI staining.

Fig 4. The detection of cell attachment to the surface of the cell culture flasks.

Fig 5. Colony forming assay.

Effect of culture medium on ATP and ROS production

Fig 6. ATP and ROS production assay.

Identification of DEGs in cells cultured in different media

Fig 7. MA plot of DEGs.

Fig 8. The gene ontology term enrichment of DEGs.

Fig 9. KEGG pathway analysis results.

Validation of the sequencing results by determining the gene expression levels

Table 2. List of differentially expressed genes in MCF7 cells cultured in αMEM vs. DMEM.

Fig 10. q-PCR–based validation of the expression patterns of selected genes from the DEGs.

Fig 11. Assessment of protein levels.

Discussion

Conclusions

Supporting information

Data Availability

Funding Statement

References

Decision Letter 0

Sadiq Umar

Roles

Author response to Decision Letter 0

Decision Letter 1

Sadiq Umar

Roles

Acceptance letter

Sadiq Umar

Roles

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

PERMALINK

RESOURCES

Similar articles

Cited by other articles

Links to NCBI Databases