The sputum samples of 20 cases were derived from 103 patients with sputum smear-positive TB in the Xinjiang region during a previous epidemiological survey conducted by the cooperative team (29). All cases were diagnosed according to China's national diagnostic criteria (30). Demographic, epidemiological and clinical data were obtained from the medical records of the patients using a unified epidemiological survey methodology. Table I provides the details of the 20 patients.

The sputum was mixed with 1–3 times the volume of a 4% NaOH (Beijing Chemical Works) solution, shaken well until dissolved and maintained at room temperature for 20 min. Once the sample was completely liquefied, 100 µl sample was aspirated and dropped evenly on the slant of modified acidic Roche's medium (Celnovte Biotechnology Co., Ltd.). Each sample was inoculated three times and placed in a 37°C incubator. After a single white colony was grown, it was picked off, placed in a 37°C incubator containing 40 ml Mycobacterium liquid medium (Shanghai Jingnuo Biotechnology Co., Ltd.) and shaken at 120 rpm for amplification. In addition, 50–100 µl frozen H37Rv (cat. no. 27294; American Type Culture Collection) bacterial solution was aspirated, added to 40 ml Mycobacterium liquid medium and amplified by shaking at 120 rpm.

An inoculation loop was dipped into the XJMTB amplified bacterial solution, applied onto a slide and fixed by heating alone. Subsequently, carbol fuchsin was added dropwise to the solution, the solution was slowly heated (but not boiled) for 3–5 min and washed with water. Hydrochloric acid-ethanol solution (3%) was then added dropwise to the solution to decolorize it for 30 sec. Finally, methylene blue was added dropwise to the solution for 0.5–1 min, after which the slide was washed, dried and observed under an optical microscope with oil immersion.

Briefly, 100 µl amplified bacilli were dropped evenly onto para-nitrobenzoic acid (PNB) and thiophene-2-carboxylic acid hydrazide (TCH) media (Celnovte Biotechnology Co., Ltd.), with each sample inoculated three times, and cultured at 37°C with 5% CO₂. Observations were made weekly, and the results were determined after 4 weeks. A single colony growing on the culture medium indicates a positive result, with negative PNB and positive TCH considered MTB infection.

For strain typing, the DNA of MTB was extracted using a bacterial DNA extraction kit (cat. no. R0017S; Beyotime Institute of Biotechnology), and the MIRU 26 fragment was amplified using a PCR kit with Taq (cat. no. D7232; Beyotime Institute of Biotechnology). The PCR thermocycling conditions were as follows: i) 94°C for 3 min (1 cycle); ii) 30 cycles at 94°C for 30 sec, 55°C for 30 sec and 72°C for 60 sec; iii) 72°C for 10 min (1 cycle), iv) maintained at 4°C. The MIRU 26 primer sequences were: Forward primer 5′-3′: TAGGTCTACCGTCGAAATCTGTGAC, reverse primer 5′-3′: CATAGGCGACCAGGCGAATAG. Agarose (cat. no. ST118; Beyotime Institute of Biotechnology) and Gel-Green (cat. no. D0143; Beyotime Institute of Biotechnology) were used to prepare 1% agarose gel, and the PCR products were electrophoresed at 130 V and observed using a Tanon-1600 Gel Image system (Tianneng Science and Technology Co., Ltd.).

The THP-1 human monocyte cell line was purchased from The Cell Bank of Type Culture Collection of The Chinese Academy of Sciences. The cells were inoculated at a concentration of 1×10⁶ cells/ml in 6-well plates (1 ml cell suspension/well) in RPMI 1640 medium (Gibco; Thermo Fisher Scientific, Inc.) supplemented with 10% fetal bovine serum (Gibco; Thermo Fisher Scientific, Inc.), and serum-free RPMI 1640 medium with an equal amount of phorbol-12-myristate-13-acetate (PMA; MedChemExpress) at a concentration of 400 ng/ml was added to induce cell differentiation into macrophages for 24 h. After removing the culture medium containing PMA, an equal volume of fresh RPMI 1640 complete culture medium was added. H37Rv and XJMTB were diluted to an OD600 of 0.6 in Mycobacterium liquid medium, and 100 µl of the fluid was added to each well to infect cells for 12, 24 and 36 h. Finally, MTB samples isolated from the sputum samples of patients numbered L3-L6 (Beijing family) were used for L group modeling in the current study. H37Rv was used for V group modeling in the current study. THP-1 cells used for transcriptome sequencing were divided into three groups: XJMTB clinical isolate-infected group (L group), H37Rv standard strain-infected group (V group) and blank control group not infected with any bacteria (C group). All cell culture conditions were as follows: 37°C, 5% CO₂.

Culture supernatants were centrifuged at 300 × g for 10 min at room temperature. Subsequently, the secretion levels of cytokines in the cell culture supernatants were measured using sandwich ELISA detection kits for IL-12p70 (cat. no. EK112), TNF-α (cat. no. EK182), IL-6 (cat. no. EK1153), IL-1β (cat. no. EK101B) and IL-10 (cat. no. EK110) [Multisciences (Lianke) Biotech, Co., Ltd.]. All operations were performed according to the manufacturer's protocol. The absorbance was measured using a microplate reader at 450 nm and compared to a standard curve.

To evaluate NO levels during MTB infection, cell culture supernatants were analyzed using the Griess assay. Culture supernatants were centrifuged at 300 × g for 10 min at room temperature. Subsequently, the supernatant (100 µl) was incubated with Griess reagent (cat. no. G4410; Sigma-Aldrich; Merck KGaA) (100 µl) at room temperature for 10 min, and the absorbance was then measured at 541 nm. Sodium nitrite was used to create a standard concentration curve.

Total RNA was extracted from the aforementioned three groups of THP-1 cells using Trizol reagent (cat. no. R0016; Beyotime Institute of Biotechnology). The extracted RNA was quantified and assessed for purity and integrity using a NanoDrop 2000 spectrophotometer (NanoDrop; Thermo Fisher Scientific, Inc.) and an Agilent 2100 Bioanalyzer (Agilent Technologies, Inc.). Subsequently, library construction was performed using TruSeq Stranded Total RNA Library Prep Kit with Ribo-Zero Gold (cat. no. RS-122-2301; Illumina, Inc.). The amount of RNA used to construct the library was 1 µg. Ribosomal RNA (rRNA) removal was performed using the Ribo-Zero Gold rRNA Removal Kit (Illumina, Inc.). Subsequently, sequencing libraries were constructed using rRNA-depleted samples. Finally, products were purified (Agencourt AMPure XP; Beckman Coulter, Inc.), and library quality was assessed using the Agilent 2100 Bioanalyzer system.

The libraries were sequenced on the Illumina HiSeq X Ten platform (Illumina, Inc.) to produce 150 bp paired-end reads. In this step, clean data (clean reads) were obtained by removing reads containing adapters and ploy-N (sequencing errors or insufficient sequencing quality) or low-quality reads from the raw data. Sequencing reads were mapped to the human genome (GRCh38) using HISAT2 (31). For mRNA, FPKM was calculated for each gene using Cufflinks (1.2) (32), and read counts were obtained for each gene using HTSeq-Count (0.12.3) (33). RNA expression profiling data were analyzed using the R (3.6.3) (https://www.r-project.org/) software package DESeq2 (1.26.0) (https://bioconductor.org/packages/release/bioc/html/DESeq2.html). The package pheatmap (1.0.12) (https://cran.r-project.org/package=pheatmap) in R (3.6.3) was used to create heat maps, whereas the package ggplot2 (3.3.5) (https://cran.r-project.org/web/packages/ggplot2/index.html) was used to create volcano maps. Bioinformatics & Evolutionary Genomics (http://bioinformatics.psb.ugent.be/webtools/Venn/) was used for creating Venn diagrams. Principal component analysis (PCA) was performed using the OECloud tools at https://cloud.oebiotech.com. The |log2 fold change|≥1 and P≤0.05 were used as criteria to screen significant DEGs for subsequent analysis. STRING (https://cn.string-db.org/cgi/input?sessionId=bTEPyYc5wXuA&input_page_show_search=off) was used to perform the protein-protein interaction (PPI) network analysis, and Cytoscape (3.8.1) (https://cytoscape.org/) and its MCODE plugin (34) was used to perform subnetwork screening and confirmation.

The Database for Annotation, Visualization, and Integrated Discovery (https://davidbioinformatics.nih.gov/) was used for functional analysis of DEGs. The significant GO biological processes and KEGG pathways with an adjusted P<0.05 were selected to analyze their biological function. The significant enrichment results were visualized using the ggplot2 (3.3.5) (https://cran.r-project.org/web/packages/ggplot2/index.html) package of R software (3.6.3).

Total RNA was extracted from cultured cells using TRIzol reagent. mRNA was reverse transcribed into cDNA using the HiScript II 1st Strand cDNA Synthesis Kit (Vazyme Biotech Co., Ltd.), according to manufacturer's protocol. qPCR was performed to measure mRNA using the ABI 7300 Plus Real-Time PCR System (Applied Biosystems; Thermo Fisher Scientific, Inc.) using the FastStart Universal SYBR Green Master Mix (Roche Diagnostics). The qPCR thermocycling conditions were as follows: i) 50°C for 2 min (1 cycle); ii) 95°C for 10 min (1 cycle); iii) 40 cycles of denaturation at 95°C for 15 sec, and annealing and extension at 60°C for 60 sec. β-actin was used as the endogenous control for mRNA expression and relative fold changes were calculated using the 2^−ΔΔCq method (35). Each RT-qPCR assay was repeated three times. The primer sequences used are shown in Table II.

Cells were lysed using RIPA buffer (MilliporeSigma) supplemented with EDTA-Free 1× Halt™ protease and phosphatase inhibitor (Thermo Fisher Scientific, Inc.). The cell lysate was then centrifuged at 14,000 × g for 15 min at 4°C and the protein concentration was determined using a bicinchoninic acid assay kit (Beyotime Institute of Biotechnology). Proteins (30 µg) were separated by SDS-PAGE on 12% gels and transferred to PVDF membranes. After blocking at room temperature for 20 min with protein-free blocking solution (Beyotime Institute of Biotechnology) and incubating overnight with antibodies against the target proteins at 4°C, as follows: BCL2 (1:2,000; cat. no. ab182858; Abcam), BAX (1:2,000; cat. no. ab32503; Abcam), caspase 3 (1:5,000; cat. no. ab32351; Abcam), cleaved-caspase 3 (1:500; cat. no. ab32042; Abcam), PARP (1:1,000; cat. no. ab191217; Abcam), cleaved-PARP (1:1,000; cat. no. ab32561; Abcam), β-actin (1:500; cat. no. ab205; Abcam), CDK1 (1:10,000; cat. no. ab133327; Abcam), p-CDK1 (Thr161) (1:1,000; cat. no. ab47329; Abcam), p53 (1:1,000; cat. no. ab32049; Abcam), p-p53 (Ser315) (1:1,000; cat. no. WL02504; Wanleibio Co., Ltd.). Horseradish peroxidase-conjugated AffiniPure goat anti-rabbit immunoglobulin G (IgG) (1:1,000; cat. no. A0277; Beyotime Institute of Biotechnology) and goat anti-mouse IgG (1:1,000; cat. no. A0216; Beyotime Institute of Biotechnology) were used as the secondary antibody and incubated at room temperature for 1 h. Primary antibody diluent (cat. no. P0023A) and secondary antibody diluent (cat. no. P0023D) were from Beyotime Institute of Biotechnology. Subsequently, after adding an appropriate amount of electrochemiluminescence chromogenic substrate (BeyoECL Star; Beyotime Institute of Biotechnology), a chemiluminescence imaging system (GeneGnome XRQ; Syngene) was used to detect the chemiluminescence, and the intensity was measured using ImageJ software (1.54f; National Institutes of Health).

Ro3306 (cat. no. SC6673; Beyotime Institute of Biotechnology) was used as a CDK1 inhibitor at a working concentration of 20 nM. Pifithrin-α (pft-α; cat. no. S1816; Beyotime Institute of Biotechnology) was employed as a p53 phosphorylation inhibitor at a working concentration of 10 µM. TC11 (cat. no. HY-129478; MedChemExpress) was used as a CDK1 activator at a concentration of 5 µM. These were dissolved in DMSO (cat. no. ST038; Beyotime Institute of Biotechnology). Briefly, after inducing THP-1 cells to differentiate into macrophages and adhere to the bottom of 6-well plates, the culture medium containing PMA was removed, and the same volume of fresh RPMI 1640 complete culture medium containing the aforementioned concentrations of the inhibitors and activator was added, followed by the addition of the bacterial solution for infection for 24 h at 37°C and 5% CO₂.

The modeling of MTB cell infection was performed as described previously (using ~1×10⁶ cells/well). Subsequently, the cells were collected, washed twice with PBS and fixed in 70% ethanol at 4°C for 24 h. The cells were then stained with 500 µl propidium iodide/RNase staining buffer (BD Biosciences) at 37°C for 15 min and cell cycle progression was detected by flow cytometry (BD FACSVerse; BD Biosciences). FlowJo (10.0.7r2; BD Biosciences) was used to analyze the results.

The apoptosis detection kit (cat. no. 556547; BD Biosciences) was used to assess the apoptosis of THP-1 cells. The modeling of MTB cell infection was performed as described previously (using ~1×10⁶ cells/well). Briefly, the cells were collected, washed twice with pre-cooled PBS, and resuspended in 1X binding buffer. Subsequently, a 100-µl cell suspension (~1×10⁵ cells) was incubated with 5 µl Annexin V-FITC and 5 µl propidium iodide at room temperature in the dark for 15 min, followed by resuspension in 400 µl 1X binding buffer and flow cytometry (BD FACSVerse; BD Biosciences). FlowJo (10.0.7r2) was used to analyze the results.

THP-1-derived macrophages infected with XJMTB were homogenized in 0.5% Triton X-100 (Beyotime Institute of Biotechnology) with 1X Halt™ Protease and Phosphatase Inhibitor SingleUse Cocktail (Thermo Fisher Scientific, Inc.). The cell lysate was centrifuged at 4°C and 13,680 × g for 20 min to obtain a clear lysate. For IP, 5 µg rabbit IgG antibody (cat. no. HY-P80879; MedChemExpress), 5 µg rabbit CDK1 antibody (cat. no. HY-P80611; MedChemExpress) and 5 µg rabbit p53 antibody (cat. no. HY-P86169; MedChemExpress) were mixed with 500 µg protein solution, and incubated overnight at 4°C. The protein A/G magnetic beads (Merck KGaA) were washed with 500 µl Cell Lysis Buffer for Western or IP (cat. no. P0013; Beyotime Institute of Biotechnology) three times. Afterwards, the mixture was mixed with 50 µl protein A/G magnetic beads and the antibody-protein A/G magnetic beads complex was gently shaken for 4 h at 4°C, and 500 µl Cell Lysis Buffer for Western or IP was then added to the precipitate. The precipitate was then eluted with 100 µl 1X SDS loading buffer at 100°C for 10 min. Finally, SDS-PAGE was performed with eluent and whole cell lysate (input), and western blotting was conducted as aforementioned.

Briefly, XJMTB-infected macrophage specimens were prepared according to the aforementioned method. The XJMTB specimens were washed with PBS to remove the extracellular bacteria. Subsequently, PBS containing 0.5% Triton X-100 was added to the cell culture dish to lyse the XJMTB-infected macrophages, and PBS containing the lysate of XJMTB-infected macrophage was diluted for 10, 100, 1,000 and 10,000 times, and inoculated onto 7H10 agar plates. The plates were incubated at 37°C for 2–3 weeks, after which the colonies were counted.

Each experiment was repeated three times. Data are presented as the mean ± SEM. Statistical comparisons were performed using two-way ANOVA or one-way ANOVA, followed by Tukey's post hoc test, or using unpaired Student's t-test. All statistical analyses were conducted using SPSS version 24.0 (IBM Corp.). P<0.05 was considered to indicate a statistically significant difference.

The isolation results in the modified acidic Roche's medium are shown in Fig. 1A, and the results of acid-fast staining are shown in Fig. 1B. The specific information and sputum features of the 20 patients are shown in Table I, including 12 male patients and eight female patients, aged 25–57 years old, with a median age of 40 years old. All patients had no history of smoking or other lung diseases, and tested negative for HIV. As shown in Table I, among the 20 patients, samples were successfully isolated and amplified from 16 patients. After PNB and TCH medium identification, 13 of them were isolated as MTB. A previous study conducted multiple-locus variable-number tandem repeat analysis strain typing and cluster analysis on the strains isolated from 103 sputum samples collected in the epidemiological survey (29), and it was revealed that most of the MTB strains prevalent in Xinjiang belonged to the Beijing MTB family (29,36,37). Rao et al (38) reported that Beijing family strains have seven repeat fragments at the MIRU 26 site (the size of the seven repeated segments is ~642 bp); therefore, this locus can be used for rapid identification of Beijing family strains. Fig. S1A shows the agarose gel electrophoresis patterns of the 13 MTB samples isolated after PCR of the MIRU 26 site, and Fig. S1B shows the cluster analysis of all strains collected by the collaborative team during the aforementioned epidemiological investigation.

The induction of NO and pro-inflammatory cytokines produced by macrophages infected with MTB can lead to DNA damage, oxidative stress and persistent inflammation (28). Therefore, the current study detected the secretion of the cytokines TNF-α, IL-1β, IL-6, IL-10 and IL-12 in macrophages infected with different MTB strains at 12, 24 and 36 h. As shown in Fig. 2, compared with those in the C group without any MTB infection, the secretion levels of these cytokines in the V and L groups were significantly increased in a dose-dependent manner. After comprehensively observing the secretion levels of cytokines at various time points, 24 h was ultimately selected as the infection time for subsequent experiments, since there was no significant difference in the secretion of most cytokines between 24 and 36 h after infection.

NO has a killing effect on MTB (39); therefore, the secretion of NO was assessed 24 h after infection. As shown in Fig. 2F, NO levels were lower in macrophages in the L group compared with those in macrophages in the V group, which may lead to enhanced survival of MTB in the L group.

To identify DEGs, transcriptome sequencing data between groups C, L and V were analyzed. The results showed that the expression levels of 2,848 mRNAs were significantly altered in the L group compared with the C group, of which 1,737 mRNAs were upregulated and 1,111 were downregulated (Fig. 3A and D). In group V compared with the C group, the expression levels of 1,678 mRNAs were significantly altered, with 1,011 upregulated and 667 downregulated mRNAs (Fig. 3B and E). The results of PCA between the three groups are shown in Fig. 3C. Furthermore, a Venn analysis was performed on the two sets of DEGs (Fig. 3F) and a follow-up analysis for the 1,527 DEGs between groups L and C was performed, since these unique 1,527 DEGs between groups L and C may reveal the specific biological processes triggered by XJMTB. GO term (Fig. 3G-I) and KEGG pathway (Fig. 3J) enrichment analyses revealed that multiple biological functions and pathways enriched by the 1,527 DEGs were associated with MTB infection, such as ‘DNA conformation change’ (40), ‘phagocytic vesicle’ (41), ‘phagocytic vesicle membrane’ (42), ‘exonuclease activity’ (43), ‘endocytosis’ (44,45), ‘neutrophil extracellular trap formation’ (46–48), ‘cellular senescence’ (49,50), ‘natural killer cell mediated cytotoxicity’ (51), ‘p53 signaling pathway’ (28,52) and ‘nucleotide excision repair’ (53).

To further explore the functions of the 1,527 mRNAs at the protein level, a PPI network (high confidence, 0.7) was established based on the results of the STRING database analysis, which consisted of 1,382 nodes and 14,264 edges. Subsequently, the plug-in MCODE in Cytoscape was used to deeply analyze the network, and the top module (score=29) was selected for subsequent research (Fig. 3K). The 33 mRNAs contained in this top module were regarded as critical mediators, and a functional analysis was performed. GO functional enrichment analysis showed that the 33 critical mediators were closely associated with ‘cell mitosis’ and the ‘cell cycle’ (Fig. 3L-N). R (3.6.3) software was applied to analyze the core genes in the PPI formed by the 1,527 genes. The top two genes were found to be CDK1 and CCNA2, and these genes were also found in the 33 key mRNAs. It has previously been shown that CDK1 and CCNA2 are closely related to the cell cycle (54). Furthermore, the previous GO and KEGG enrichment analyses showed that the unique 1,527 DEGs between groups L and C were enriched in terms of ‘DNA replication’ and other cell cycle related terms and pathways. Subsequently, RT-qPCR was used to detect the mRNA expression levels of CDK1 and CCNA2 (Fig. 3P), which showed significant differences between the L and C groups. Given that the mRNA expression levels of CDK1 in each group were consistent with the results of the bioinformatics analysis, and that the number of interaction nodes between CDK1 and other genes ranked first in Fig. 3O, CDK1 was identified as the target gene for subsequent studies.

CDK1 is an enzyme necessary for initiating mitosis after the end of S-phase, and it can regulate the G₂/M checkpoint (17) and is closely related to apoptosis (18). Therefore, flow cytometry was performed to detect differential changes in the cell cycle of macrophages before and after infection with different sources of MTB. As shown in Fig. 4A-F, compared with in group C, groups V and L exhibited significantly higher G₂/M cell cycle blockage, and the ratio of cell cycle blockage was significantly higher in groups L3-5 than that in in group V, suggesting that macrophages infected with MTB could trigger G₂/M cell cycle block and that different sources of MTB could induce distinct degrees of cell cycle arrest. Notably, macrophages infected with XJMTB may trigger a more severe G₂/M cell cycle block compared with those infected with H37Rv.

The current study next examined the apoptosis of macrophages after infection with different sources of MTB using western blotting and flow cytometry. Compared with those in group C, the protein expression levels of BCL2 were decreased in groups L and V, whereas the protein expression levels of BAX and cleaved-caspase 3 (Fig. 4G and H), and cleaved-PARP (Fig. S2) were increased. Compared with that in group C (Fig. 4I), groups V (Fig. 4J) and L (Fig. 4K-M) exhibited marked apoptosis, with the degree of apoptosis being significantly stronger in group L than that in group V (Fig. 4N). These findings suggested that MTB could induce macrophage apoptosis, but the degree of macrophage apoptosis after infection with different sources of MTB varied, with the proportion of apoptotic macrophages infected with XJMTB being higher compared with those infected with H37Rv.

Next, the CDK1 inhibitor Ro3306 was used to inhibit the expression of CDK1 in macrophages after infection with different sources of MTB. The expression of CDK1 was first detected in group L before and after the addition of Ro3306, as shown in Fig. 5A and B. The findings indicated that the working concentration provided in the Ro3306 manual could effectively inhibit the expression of CDK1. The results of the flow cytometric analysis showed that the percentages of G₂/M cell cycle arrest in macrophages in the V group (Fig. 5C and G), L3 group (Fig. 5D and H), L4 group (Fig. 5E and I) and L5 group (Fig. 5F and J) were significantly decreased after the addition of Ro3306 (Fig. 5S). These results suggested that inhibiting CDK1 expression could attenuate the G₂/M cell cycle block of macrophages caused by infection with MTB.

Similarly, the effects of the CDK1 inhibitor Ro3306 on macrophage apoptosis were examined after infection with different sources of MTB. The results of flow cytometry showed that the percentages of apoptotic macrophages in the V group (Fig. 5K and O), L3 group (Fig. 5L and P), L4 group (Fig. 5M and Q) and L5 group (Fig. 5N and R) were significantly decreased after the addition of Ro3306 (Fig. 5T). Furthermore, the results of western blotting showed that the protein expression levels of BCL2 were increased by Ro3306, whereas the protein expression levels of BAX and cleaved-caspase 3 (Fig. 5U and V), and cleaved-PARP (Fig. S3) were decreased. These findings suggested that inhibiting CDK1 expression could attenuate macrophage apoptosis caused by MTB infection.

The aforementioned results indicated that macrophages infected with MTB could induce G₂/M cell cycle block and apoptosis, but the degree of cell cycle arrest and apoptosis induced by different sources of MTB varied. The proportion of G₂/M cell cycle block and apoptosis in macrophages infected with XJMTB was significantly higher compared with that in macrophages infected with H37Rv. Furthermore, the degree of apoptosis and G₂/M cell cycle arrest in macrophages infected with H37Rv or XJMTB was alleviated after inhibiting CDK1 expression, which was consistent with the predicted result of the bioinformatics analyses, suggesting that CDK1 may be a key regulatory gene for G₂/M cell cycle arrest and apoptosis in macrophages with MTB infection.

Since the ‘p53 signaling pathway’ was revealed to be enriched in the aforementioned KEGG analysis, and it is well known that CDK1 can interact with p53 to affect cell cycle progression and apoptosis (55), the current study examined the expression of p53 in macrophages after infection with different sources of MTB. As shown in Fig. 6A and B, the expression levels of p53 were significantly elevated after infection with different sources of MTB, but there was no significant difference between the two infection groups, suggesting that the G₂/M cell cycle arrest and apoptosis caused by high expression of CDK1 after MTB infection was not achieved by directly affecting p53 expression.

Fogal et al (56) demonstrated that CDK1 could mediate the phosphorylation of p53 at the Ser315 site to affect apoptosis, and indicated that the expression of total p53 may not change during this process. Therefore, the present study examined the phosphorylation of p53 at the Ser315 site in macrophages infected with different sources of MTB. The results showed that the phosphorylation of p53 at the Ser315 site was higher in macrophages infected with XJMTB than in those infected with H37Rv (Fig. 6A and B), suggesting that the G2/M cell cycle arrest and apoptosis caused by high expression of CDK1 after infection with MTB might be mediated by the phosphorylation of p53 at the Ser315 site.

Subsequently, the p53 inhibitor pft-α was used to inhibit the phosphorylation of p53. The expression of p53 and the phosphorylation of p53 (Ser315) before and after the addition of pft-α is shown in Fig. 6C and D. The findings indicated that the working concentration recomeded in the pft-α instruction manual could effectively inhibit the phosphorylation of p53 (Ser315). The results of flow cytometric analysis revealed that the percentages of G₂/M cell cycle block in macrophages in the V group (Fig. 6E and I), L3 group (Fig. 6F and J), L4 group (Fig. 6G and K) and L5 group (Fig. 6H and L) were decreased after the addition of pft-α (Fig. 6U). These findings indicated that inhibiting the phosphorylation of p53 (Ser315) could attenuate the G₂/M cell cycle arrest caused by MTB infection.

The current study then examined the effect of pft-α on the apoptosis of macrophages after infection with different sources of MTB. The results of flow cytometric analysis showed that the percentages of apoptotic macrophages in the V group (Fig. 6M and Q), L3 group (Fig. 6N and R), L4 group (Fig. 6O and S) and L5 group (Fig. 6P and T) were decreased after the addition of pft-α (Fig. 6V). The western blot analysis showed that the protein expression levels of BCL2 were increased after the addition of pft-α, whereas the protein expression levels of BAX and cleaved-caspase 3 (Fig. 6W and X), and cleaved-PARP (Fig. S4) were decreased. The two experiments suggested that inhibiting the phosphorylation of p53 (Ser315) could attenuate macrophage apoptosis due to infection with MTB.

The aforementioned results indicated that infection with MTB could induce elevated p53 expression; however, there was no significant difference in p53 expression among macrophages infected with different sources of MTB, whereas there was a difference in the phosphorylation of p53 (Ser315). The degree of macrophage apoptosis and G₂/M cell cycle arrest caused by infection with different sources of MTB was alleviated by inhibiting the phosphorylation of p53 (Ser315), which was consistent with the predicted result of the bioinformatics analysis, suggesting that p-p53 may be a key regulatory protein for G₂/M cell cycle block and apoptosis in macrophages infected with MTB. Therefore, it was hypothesized that a regulatory relationship may exist between CDK1 and p-p53.

The present study revealed that the secretion levels of TNF-α, IL-6, IL-12, IL-10 and IL-1β were increased after MTB infection of macrophages. Therefore, the secretions of TNF-α, IL-6, IL-12, IL-10, IL-1β and NO were examined before and after inhibiting CDK1 expression or p53 (Ser315) phosphorylation. As shown in Fig. 7, in macrophage models infected with MTB from different sources, inhibition of CDK1 expression (MTB + Ro3306) or p53 (Ser315) phosphorylation (MTB + Pft-α) resulted in a significant decrease in the secretion of TNF-α, IL-6, IL-12, IL-10 and IL-1β, but no change in NO secretion. These results indicated that inhibiting CDK1 expression or p53 (Ser315) phosphorylation may suppress the release of inflammatory cytokines in THP-1-derived macrophages infected with MTB.

To verify whether CDK1 could affect G₂/M cell cycle arrest and apoptosis due to MTB infection by regulating the phosphorylation of p53 (Ser315), western blotting was performed to examine the phosphorylation of p53 (Ser315) following the addition of Ro3306 to XJMTB-infected macrophages to inhibit the expression of CDK1. As shown in Fig. 8A and D, after the addition of Ro3306, the phosphorylation of p53 (Ser315) was subsequently decreased.

Subsequently, TC11 (an activator of CDK1) was used to activate CDK1. TC11 functions as a phenylacetylamide derivative and is structurally related to immunomodulatory active drugs, such as thalidomide, lenalidomide and pomalidomide (57). TC11 can induce MCL1 degradation and activate caspase 9 and CDK1, leading to cell apoptosis (58,59). Fig. 8B and E showed that TC11 could enhance the phosphorylation of CDK1 (Thr161), and the phosphorylation of p53 (Ser315) was also increased. Moreover, inhibiting the phosphorylation of p53 (Ser315) did not alter CDK1 expression (Fig. 8C and F). Therefore, it was hypothesized that CDK1 could regulate p53 (Ser315) phosphorylation in macrophages infected with XJMTB.

Next, cell cycle progression and apoptosis were examined in three situations: i) Activation of CDK1 only; ii) inhibition of p53 (Ser315) phosphorylation only; iii) and activation of CDK1 + inhibition of p53 (Ser315) phosphorylation. The aforementioned results revealed that elevated CDK1 expression and enhanced p53 phosphorylation levels led to G₂/M cell cycle arrest. TC11 can activate CDK1, whereas pft-α can inhibit p53 (Ser315) phosphorylation. The results of flow cytometry showed that the proportion of G₂/M cell cycle arrest in macrophages with CDK1 activation and p-p53 (Ser315) inhibition (Fig. 8I) was higher than that in macrophages with p-p53 (Ser315) inhibition alone (Fig. 8H), but lower than that in those with CDK1 activation (Fig. 8J). These findings indicated that the inhibitory ability of pft-α on p53 (Ser315) phosphorylation was weakened by TC11, thus suggesting that the CDK1 activation caused by TC11 could reverse the reduction in the proportion of G₂/M cell cycle block caused by the inhibition of p53 (Ser315) phosphorylation in macrophages infected with XJMTB.

As expected, flow cytometry results showed that the proportion of apoptosis in macrophages in which CDK1 was activated and p53 phosphorylation was inhibited (Fig. 8M) was higher than that in macrophages in which only p53 phosphorylation was inhibited (Fig. 8L), but lower than that in macrophages in which only CDK1 was activated (Fig. 8K). Fig. 8N shows the apoptosis ratio in each group. Furthermore, the results of western blotting were consistent with those obtained by flow cytometry (Figs. 8O, P and S5). These findings suggested that TC11-induced CDK1 activation could reverse the reduction in the proportion of apoptosis caused by the inhibition of p53 (Ser315) phosphorylation in macrophages infected with XJMTB.

To clarify whether this regulatory relationship affected the survival of XJMTB in macrophages, XJMTB survival was assessed in macrophages under the aforementioned three conditions. As shown in Fig. 8Q, the survival rate of XJMTB in macrophages with CDK1 activation and p-p53 (Ser315) inhibition was higher than that in macrophages with p-p53 (Ser315) inhibition, but lower than that in those with CDK1 activation. These data strongly suggested that CDK1 activity influenced p53 phosphorylation levels.

To clarify the relationship between CDK1 and p53 in macrophages infected with XJMTB, Co-IP experiments were performed to observe whether they could interact with each other. The results showed that there was an interaction between CDK1 and p53 (Fig. 8R). CDK1 is a kinase that can transfer phosphate groups, thus it may be hypothesized that CDK1 can directly regulate p53 phosphorylation. Based on the aforementioned results in an in vitro model of XJMTB infected-macrophages, the high expression of CDK1 could enhance the phosphorylation of p53 (Ser315), affect the secretion of TNF-α, IL-6, IL-10, IL-1β and IL-12, promote G₂/M cell cycle arrest and apoptosis of macrophages, and enhance the survival of XJMTB in macrophages.