Introduction

Tobacco smoking is one of the major preventable causes of premature deaths globally and is a potentially acquired risk factor for cardiovascular diseases (CVDs), chronic obstructive pulmonary disease, and cancer [1,2,3]. The scientific literature suggests tobacco smoking to be a causative agent for CVDs and cancers [2]. According to the World Health Organization, tobacco kills more than 8 million people each year worldwide, including around 1.3 million people who do not smoke but are exposed to second-hand smoke.

There are more than 7000 chemicals in cigarette smoke, of which 250 are harmful, and 69 are well-established carcinogens [3, 4]. The constituents of cigarette smoke generate oxidative stress, which can subsequently cause DNA damage, leading to stress-induced premature cellular senescence [4,5,6]. Cellular senescence is characterized by cell cycle arrest, macromolecular damage, metabolic dysfunction, and a shift in the expression of secondary markers [7, 8]. Transient cellular senescence can exert a beneficial impact, such as wound healing and tumor suppression [6, 9]. However, the chronic accumulation of senescent cells can impair wound healing, accelerate aging, promote inflammation, and give rise to chronic diseases such as CVDs, cancer, and neurodegenerative diseases [9,10,18]. Therefore, it can be postulated that through mitigating the expression of SASP factors (Fig. 3; Table 2) [23,24,25,26,27], colchicine can suppress the initiation and progression of CVDs [22, 23, 25] and metastasis, angiogenesis, and growth in cancers [42].

Our pathway analysis showed that tobacco smoke condensate activated NF-κB (Fig. 4) and MAPKs P38 and ERK (Fig. 5). It has already been reported that DNA damage, oxidative stress, and ethanol can activate these pathways [21, 26, 27, 38, 39]. Activation of these pathways has been linked to cellular senescence, and inhibiting these pathways could block cellular senescence [21]. After activation, these pathways enhance the transcription, protein expression, and stability of senescence-driving proteins such as P53 and P21 [21, 37, 43, 44]. Moreover, MAPKs P38 and ERK increase the levels of SASP factors through NF-κB transcriptional activity [21]. The activation of P38 is needed for NF-κB transcriptional activity in senescence [45]. Interestingly, colchicine, without significantly affecting p-mTOR expression, increased the relative protein expression of mTOR downstream signalling molecules p-S6 and p-4EBP-1 (Fig. 6). These two downstream signalling molecules have the opposite effect on life span [46,47,48]. S6K deficiency in mice and flies extended mean life span [46, 48] and 4EBP-1 overexpression in flies increased life span [47]. Therefore, the net effect of colchicine through mTOR pathway activation would be challenging to determine. Taken together, it is very likely that by blocking NF-κB, P38- and ERK (Figs. 4 and 5) [15, 21, 26, 27, 44], colchicine suppressed senescence and the expression of SASP factors in endothelial cells (Figs. 2 and 3) treated with tobacco smoke condensate.

Conclusion

Tobacco smoking is one of the potential acquired causative risk factors for chronic and age-related diseases. Colchicine prevented tobacco smoke condensate-induced DNA damage and senescence in endothelial cells exposed to smoke condensate. It mitigated the expression of SASP factors in endothelial cells treated with tobacco smoke condensate. Colchicine blocked tobacco smoke-condensate-induced activation of NF-κB, P38, and ERK. These findings suggest that by suppressing the activation of NF-κB and MAPKs, colchicine inhibited senescence in endothelial cells treated with tobacco smoke condensate. The current findings will have implications in cardiovascular diseases.

Materials and methods

Cell Culture

Three different HUVEC models were procured from Promocell (Heidelberg, Germany). Endothelial cell medium (C-22,010, Promocell, Heidelberg, Germany) containing endothelial growth factors (C-39,215, Promocell, Heidelberg, Germany) was used to maintain endothelial cells at 37 °C in a humidified environment at 37 °C and 5% CO2. Upon arrival, the cells were thawed and seeded in T75 culture flasks. The cells were passaged when they reached 80–90% confluence. For passaging, the cells were washed with PBS and incubated with trypsin for 4 min at 37 °C in a humidified environment at 37 °C and 5% CO2. The cells were seeded at a density of 5000 cells/cm2 in new cell culture plates. All experiments were performed at passage 7. The cells were treated with either 50 µg tobacco smoke condensate, 50 nm colchicine or tobacco smoke condensate combined with colchicine. Untreated cells were used as control. All experiments were performed with three biological replicates except Lamin B1 and DCFH-DA staining, where one HUVEC cell model was used.

Tobacco smoke condensate preparation

Commercially available cigarettes were smoked through ethanol. After that, ethanol was evaporated at room temperature. Tobacco smoke condensate was weighed, and 100 mg/mL of tobacco smoke condensate was dissolved in DMSO.

DCFH-DA staining

To investigate the accumulation of cellular ROS, 5000 cells/cm2 endothelial cells were seeded in a 96-well plate. The next day, the medium was changed with a new medium either containing 50 µg/mL tobacco smoke condensate, 50 nM colchicine, or 50 µg/mL smoke condensate combined with 50 nM colchicine. Endothelial cell medium alone was used as a control. After 2 h of treatment, 10 µM of the fluorescence probe 2,7-dichlorofluorescein diacetate (DCFH-DA, D6883, Sigma-Aldrich, MO, USA) was added to the cells. The cells were incubated with DCFG-DA at 37 °C for 30 min in the dark. The cells were washed three times with a serum-free medium. The images were taken with a fluorescence microscope and analyzed with image J.

Immunofluorescence staining

The cells were treated with different conditions (as described in the previous section) for 2 h for 8-OHDG staining and 24 h for Lamin B1 staining. After washing cells thrice with PBS, the cells were fixed with 4% paraformaldehyde for 10 min at RT. After washing cells thrice with PBS, for permeabilization, the cells were treated with 0.2% Triton™ X-100 at RT for 10 min. For blocking, the cells were incubated with 5% bovine serum albumin (BSA) at RT for 1 h. The cells were incubated overnight with primary antibodies 8-OHDG (Supplementary table S1) and Lamin B1 (Supplementary table S1) at 4° C. The next day, after washing cells thrice with PBS, the cells were incubated with secondary antibodies (Supplementary table S1) for 1 h at RT. HOECHST (Sigma-Aldrich) was used for nuclear staining. The images were captured using a Leica DMi8 Inverted Microscope and the compatible LAS-X Life Science Microscope Software (Leica Application Suite X) Platform. The images were analyzed using ImageJ (version 1.53c) (National Institutes of Health, Bethesda, MD, USA).

Western blot

For protein analysis, HUVECs were treated with 50 µg/mL smoke condensate, 50 nM colchicine, or 50 µg/mL smoke condensate combined with 50 nM colchicine for 24 h. Untreated endothelial cells were used as controls. RIPA buffer was used for total protein extraction. DC Protein Assay Kit (500–0116, Bio-Rad, Hercules, CA, USA) was used to quantify protein concentration. Subsequently, 30 µg of total protein under reducing conditions was loaded onto a 12% sodium dodecyl sulfate-polyacrylamide gel. For the first 20 min, electrophoresis was conducted at 60 Volts, followed by 110 Volts for 30–60 min. The separated proteins were then transferred onto a 0.45 μm pore –size nitrocellulose membrane at 250 mA for 120 min. The membranes were blocked for one hour with a 5% bovine serum albumin (BSA) solution in 0.05% TBST to minimize nonspecific binding. After that, the membranes were incubated with primary antibodies (see Supplementary Table S1) in 5% BSA overnight at 4 °C on a shaking platform. Afterward, the membranes underwent 3 × 10 min washes with TBST and were subsequently exposed to secondary antibodies diluted in 0.05% TBST (refer to Supplementary Table S1) for one hour at room temperature. Densitometry analysis was performed using NIHImageJ with β-actin correction.

Quantitative polymerase chain reaction (qPCR)

For qPCR analysis, the endothelial cells were treated as described in the previous section. Total RNA was extracted using the Nucleo Spin RNA kit (740955.50, MACHEREY-NAGEL, Düren, Germany) according to the manufacturer’s instructions. A total of 1.2 µg of RNA was utilized for reverse transcription, accomplished using the MMLV Reverse Transcriptase kit (M1701, Promega, Walldorf, Germany), Random Hexamer Primers (48,190,011, Thermo Fisher), and RiboLock RNase Inhibitor (EO0384, Thermo Fisher). The qPCR was run using total cDNA combined with AceQ SYBR qPCR Master Mix (Q111-03, Vayzme, Nan**g, China) and primers (Supplementary Table 2) on a Bio-Rad thermal cycler. The thermal cycling program consisted of an initial denaturation step at 95 °C for 8 min, followed by 40 cycles of 95 °C for 15 s, 58.9 °C for 30 s, and 72 °C for 30 s, concluding with a melting curve analysis. To calculate relative mRNA expressions, data were normalized to β-actin expression, and the relative expression levels were quantified using the comparative ΔCT method.

Senescence associated β-Galactosidase staining

For senescence associate beta-galactosidase (SA-β-Gal) staining, endothelial cells were treated for 24 h as described in the previous sections. SA β-Gal staining was performed using the Senescence Cells Histochemical Staining Kit (GALS, Sigma, MO, USA) following the manufacturer’s instructions. The cells were incubated with SA–-β-galactosidase staining solution at 37 °C for seven hours. The staining solution was aspirated and the cells were overlaid with 70% glycerol in PBS. After staining, the cells were stored at 4 °C. The images were captured using a Leica DMi8 Inverted Microscope and the compatible LAS-X Life Science Microscope Software (Leica Application Suite X) Platform. The images were analyzed using ImageJ (version 1.53c) (National Institutes of Health, Bethesda, MD, USA).

Statistical analysis

We analyzed the data on PRISM using one-way ANOVA followed by Tukey’s post hoc test.