Modulation of the Molecular Biological Profile of Breast Cancer Cells by Exposure to Bifidobacterium Аnimalis

Modulation of the Molecular Biological Profile of Breast Cancer Cells by Exposure to Bifidobacterium Аnimalis | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Modulation of the Molecular Biological Profile of Breast Cancer Cells by Exposure to Bifidobacterium Аnimalis Petro Virych, Natalia Bezdieniezhnykh, Oleksandra Lykhova, Oleksandr Mushii, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9441737/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 11 You are reading this latest preprint version Abstract Background: The microbiota is an important element of the tumor microenvironment and is able to influence the biological properties of malignant cells, which determine their malignancy and sensitivity to anticancer therapy. Aim : To investigate the effect of the microbiota member Bifidobacterium animalis (B. animalis) on glucose metabolism, the expression of genes regulating these processes, ROS levels, and the expression of EMT-associated proteins in breast cancer (BC)cells of different molecular subtypes. Materials and methods: BC cell lines: T47D, MCF-7, MDA-MB-231; prokaryotic cells: Bifidobacterium animalis subsp. lactis BB-12 . Metabolic activity of BC cells was determined by biochemical methods. Expression levels of glucose transporters and key enzymes of glycolysis genes were assessed by real-time PCR. Viability of BC cells and ROS production were determined by flow cytometry. Expression of EMT-associated proteins was analyzed by immunocytochemical analysis. Results: BCcells treated with B. animalis are characterized by a shift in the metabolic profile towards increased glycolysis, inhibition of proliferation and induction of changes in the redox state of cells.A statistically significant increase in glucose consumption and lactate production rate, lactate dehydrogenase activity was observed in B. animalis-treated BC cells of all three lines. The detected changes in mRNA expression of the glucose transporter genes GLUT1 and GLUT4 and the lactate dehydrogenase isoforms LDHA and LDHB confirm that B. animalis does not simply modulate individual metabolic or signaling pathways, but triggers a complex reprogramming of BC cells in a direction characteristic of their molecular subtype. In B. animalis-treated BCcells G6PD activity correlates with the level of ROS production in a feedback loop. The multidirectional influence of prokaryotic members of the microbiome was also revealed when studying the EMT-associated profile of breast cancer cells of different molecular subtypes: the expression of biomarkers differed depending on the initial dominance of epithelial or mesenchymal characteristics. Conclusions: The data support the concept that bifidobacteria can act as modulator of the tumor microenvironment and metabolic plasticity of breast cancer cells, and open prospects for further study of bacterial metabolites as potential regulators of tumor growth, their metastatic properties, and response to therapy. breast cancer cell culture Bifidobacterium animalis epithelial-mesenchymal transition glucose metabolism apoptosis Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Introduction Characteristics typical of cells with a malignant phenotype include unlimited capacity for replication, evasion of apoptosis, insensitivity to growth-inhibiting signals, tissue invasion, and metastasis. In order for malignant cells to obtain the energy and materials necessary to maintain these characteristics, they must undergo reprogramming of their metabolic pathways [ 1 ]. This reprogramming results in increased glucose uptake, lactate accumulation, lipid metabolism disorders, and other changes, which is an adaptive process necessary for cell expansion and persistent signals for proliferation to meet the survival needs of tumor cells in specific microenvironments [ 2 ]. The key driver in the spread of tumor cells and their adaptation to a new microenvironment, i.e. their acquisition of a metastatic phenotype, is the process of epithelial-mesenchymal transition [ 3 , 4 ]. The EMT program is activated by a number of signals, in particular, the influence of growth factors, various cytokines, primarily of stromal origin. During a malignant process, the system of signaling cascades initiated in the system of the tumor microenvironment is unbalanced, which stimulates the progression of the disease [ 5 , 6 ]. Metastatic cells adjust their metabolism accordingly to adapt, and part of the genetic reprogramming orchestrated by EMT affects the expression of metabolic genes, regulating glucose, lipid, glutamine, and nucleotide metabolism. However, the extent of this reprogramming of the metabolic network remains unclear. Further questions about the relationship between EMT and the altered metabolic profile of tumor cells have been raised by the discovery that oncogenic mutations in certain metabolic enzymes (fumarate hydratase, succinate dehydrogenase, and isocitrate dehydrogenase), drive EMT [ 7 , 8 ]. At the same time, according to the authors, it is shown that tumor cells with a dominant mesenchymal phenotype have different metabolic needs compared to their epithelial counterparts to meet the metabolic needs of increased motility and invasion. Thus, according to Shaul and colleagues, mesenchymal cells demonstrate high levels of expression of 44 metabolic genes. It was found that these genes are also upregulated upon induction of EMT by expression of Twist1 in human mammary epithelial cells [ 7 , 9 ]. However, the mechanism of such regulation is currently unknown. According to known data and our previous studies, certain members of probiotic strains, namely Bifidobacterium , may act as modifiers of the metabolism of tumor cells in general and breast cancer (BC) cells in particular. It has been shown that co-cultivation of BC cells with Bifidobacterium animalis is accompanied by changes in the processes of glucose metabolism in malignant cells, in particular, increased glycolysis [ 10 ]. Such facts open up the following questions and the formation of the next stages for studying the role of certain components of the microenvironment, which already includes the microbiome, as a regulator of both the metabolic profile and the metastatic phenotype of malignantly transformed cells. Therefore, in this manuscript, we will consider the effect of co-cultivation of Bifidobacterium animalis with BC cells on the modification of metabolic and phenotypic characteristics of tumor cells, in particular those associated with their malignant properties. Materials and methods Cells. Human BC cells of T47D, MCF-7 (luminal subtype) and MDA-MB-231 (basal subtype) cell lines were obtained from the Bank of Cell Lines from Human and Animal Tissues of the R.E. Kavetsky Institute of Experimental Pathology, Oncology and Radiobiology of the NAS of Ukraine (Registration Certificate, series AN No. 41 dated 19.02.2009). BC cells were cultured in DMEM culture medium containing 4 mmol/L L-glutamine (BioWest, France), 10% fetal bovine serum (FBS) (BioWest, France) and 1x penicillin-streptomycin (BioWest, France). Cells were incubated at 37°C in a humidified atmosphere supplied with 5% CO 2 . The medium changing and cell passaging were performed according to standard procedures [ 11 ]. Cells were passaged after they reached 80% − 90% confluency using Versene's solution (Vetline Agroscience, Ukraine) and Trypsin – EDTA 1X in PBS (BioWest, France). Cells in exponential growth phase were used in the experiments. Bacteria. Live lyophilized cells of Bifidobacterium animalis subsp. lactis BB-12 isolated from a probiotic produced by Lek Pharmaceuticals, Ljubljana, Slovenia (Linex Baby, Sandoz, PT1042), were used in the study. Bacterial cells were diluted in DMEM without antibiotic. Co-cultivation of BC cells and live B. animalis under the condition of their direct interaction. BC cells were seeded in 75 cm 2 plastic flasks at a number of 1x10 6 . Cells were planted in DMEM with 10% FBS without antibiotic. Cells were incubated at 37°C in a humidified atmosphere with 5% CO 2 for 10 hours, after which the medium was completely changed and bacteria were added in a ratio of eukaryotic/bacterial cells of 1/400. Cells were incubated at 37°C and 5% CO 2 for 72 hours. BC cells, which were cultured under standard conditions without bacteria, were used as a control for eukaryotic cells. The medium after incubation was collected for further measurement of glucose and lactate concentrations. The number of live BC cells was determined by trypan blue assay (Appliсhem, Germany), the cells were lysed in RIPA buffer [ 12 ] supplemented with protease inhibitor cocktail (Sigma-Aldrich, USA) and used to measure the activities of intracellular lactate dehydrogenase (LDH) and glucose-6-phosphate dehydrogenase (G6PD). Determination of glucose consumption rate and lactate production rate. The studied parameters were determined using the automatic analyzer GBG ChemWell 2900 (Awareness Technology, USA). To determine the glucose concentration, a colorimetric enzymatic method with glucose oxidase was used, and to determine the lactate concentration, an enzymatic method using lactate oxidase was used. The determination was performed using the diagnostic kits “Glucose (Ox) Liquid” (MedTest Dx, Pointe Scientific, USA) and “Lactate” (Greiner Diagnostic GmbH, Germany) according to the manufacturer’s instructions. The glucose metabolism indicators of BC cells – the rate of glucose consumption (GCR) and lactate production (LPR) – were determined using the formulas [ 13 ]: $$\:GCR=2\times\:\frac{\left({C}_{gl}\left({t}_{i}\right)-{C}_{gl}\left({t}_{i+1}\right)\right)\times\:V}{N\left({t}_{i}\right)+N\left({t}_{i+1}\right)}$$ $$\:LPR=2\times\:\frac{\left({C}_{L}\left({t}_{i+1}\right)-{C}_{L}\left({t}_{i}\right)\right)\times\:V}{N\left({t}_{i}\right)+N\left({t}_{i+1}\right)}$$ where concentrations of glucose and lactate at two consecutive days ( t i and t i+1 ) of cell growth are marked as C gl (t i+1 ), C L (t i ), C L (t i+1 ); N(t i ) , and N(t i+1 ) are the counts of ВC cells on corresponding consecutive days of growth; V is the volume of the incubation medium per well. Measurement of intracellular LDH and G6PD activities. Enzyme activities were measured in BC cells lysates. The resulting lysates were centrifuged in a high-speed refrigerated centrifuge (Sigma, USA) at 13,000 rpm and 4°C for 15 min. The collected supernatant was used to analyze the enzyme activities. A kinetic method using L-lactate from a Lactate Dehydrogenase Set (Pointe Scientific, USA) and glucose-6-phosphate from a Glucose-6-Phosphate Dehydrogenase Set (MedTest Dx, Pointe Scientific, USA) was used. Both analyses were performed according to the manufacturer’s instructions. The enzyme activities were calculated based on the number of cells in each sample. Determination of BC cell death indices. The percentage of viable, apoptotic and necrotic cells was determined using Annexin V conjugated to the fluorescent dye FITC and propidium iodide (PI) using the Annexin V - FITC Apoptosis Detection Kit (Dojindo, Japan). BC cells were detached from the substrate with trypsin solution (Biowest, France), washed three times with PBS and stained according to the kit manufacturer’s protocol. Results were obtained using a DxFlex flow cytometer (Beckman Coulter) equipped with a 488 nm blue laser. Annexin V-FITC staining was analyzed in the FITC channel, and PI staining was analyzed in the ECD channel. Apoptosis/necrosis parameters were assessed using a four-quadrant gate on a FITC-A/ECD-A dot matrix with gate position adjustment for samples stained with either annexin or PI alone. At least 10,000 events were analyzed for each sample. Data analysis was performed using CytExpert for DxFlex software. Immunocytochemical analysis. Coverslips with BC cells, following incubation with B. animalis were fixed with a 1:1 solution of methanol (Merck, Germany) and acetone (Khimrezerv, Ukraine) for 2 hours at -20°C and then washed three times with cold PBS (BioWest, France). The immunocytochemical reaction was performed using a Master Polymer Plus Detection System (Peroxidase) kit (Vitro SA, Spain). The reaction was carried out according to the manufacturer's instructions. The coverslips were covered with Vimentin, E-cadherin and β-catenin primary antibodies (Vitro SA, Spain) and left to incubate for 1 hour at room temperature. After the reaction, the coverslips were stained with hematoxylin and eosin solution (Sigma, USA) and fixed in Faramount Aqueous Mounting Medium (Thermo Fisher Scientific, USA). The resulting preparations were analyzed by counting cells with expression (brown), taking into account the color intensity, using a Axiostar Plus light microscope (Carl Zeiss, Germany) at x400 magnification, and photographed with a digital camera (Canon PowerShot G5, UK) at a x1000 magnification. At least three random fields of view were analyzed. Expression was assessed using the H-Score [ 14 ]. Real-time reverse transcription PCR. The total RNA pool from human BC cells was isolated using the commercial “RNeasy Plus Mini Kit” (QIAGEN, Germany) according to the manufacturer’s protocol. The amount of isolated RNA was determined on a “NanoDrop 2000c Spectrophotometer” (ThermoScientific, USA). To study mRNA expression, cDNA was synthesized from 100ng of total RNA using the LunaScript® RT SuperMix Kit (New England Biolabs, Inc., USA) for reverse transcription. The primer sequences for mRNA detection of the studied genes were obtained using the resource https://www.ncbi.nlm.nih.gov/tools/primer-blast and synthesized by Metabion, Germany (Table 1 ). A quantitative real-time PCR was performed on a QuantStudio 5 Dx Real-Time PCR System (Thermo Fisher Scientific, USA) using a LunaScript® MasterMix Kit (New England Biolabs, USA). β-actin mRNA was used as an endogenous control to determine mRNA expression. Table 1 Primer sequences for mRNA expression Gen Primer GLUT1 Forvard TTG CAG GCT TCT CCA ACT GGA C Reverse CAG AAC CAG GAG CAC AGT GAA G GLUT4 Forvard ACG AGG CTT CTT CTA CAC ACC C Reverse TCC ACA ATG CCA CGC TTC TGC A G6PD Forvard CTG TTC CGT GAG GAC CAG ATC T Reverse TGA AGG TGA GGA TAA CGC AGG C LDHA Forvard GGA TCT CCA ACA TGG CAG CCT T Reverse AGA CGG CTT TCT CCC TCT TGC T LDHB Forvard GGA CAA GTT GGT ATG GCG TGT G Reverse AAG CTC CCA TGC TGC AGA TCC A The threshold cycle was averaged across all replicates of each sample. Expression differences between the mRNAs tested relative to the control were calculated using the formula 2- ΔCt . The error bars for the expression difference calculations show the range of ΔCt values based on including the standard deviation in these values ​​(ΔCt = Ct(mRNA of the test gene)-Ct(mRNA β-actin)) Statistical analysis. The experiments were performed three times. The mean value of the studied indicators (M), standard deviation (SD) and Welch's t-test were calculated using the GraphGad Prism 8.0.1 software package. Differences were considered statistically significant at p < 0.05. Results BC cells were treated with B. animalis for 72 hours and the viability, redox status and metabolic profile of these cells were analyzed. The results obtained at this stage allowed us to assess the differences in the proliferative and glycolytic activity of the original and bifidobacteria-treated tumor cells of different molecular subtypes. In the trypan blue test, it was shown that B. animalis causes a statistically significant decrease in the number of viable cells of the T47D line by 43%, MCF-7 by 52% and MDA-MB-231 by 26%, compared to control cells (Fig. 1 ). At the same time, a comparative analysis of the percentage of apoptotic cells in the population of intact and B. animalis -treated BC cells of all three lines did not reveal a statistically significant difference in the studied indicators (Fig. 2 ). The metabolic profile of BC cells after co-cultivation with B. animalis was studied by analyzing a set of biochemical parameters associated with glycolysis. In particular, the GCR and LPR, the activity of LDH and G6FD. In T47D and MCF-7 cells of the luminal subtype treated with B. animalis , GCR was statistically significantly increased by 2–2.2 times, respectively, compared with intact cells. In basal subtype MDA-MB-231 cells treated with B. animalis , an increase of this indicator by 1.8 times was also observed compared to control (Fig. 3 a). Also, in BC cells of all three lines treated with B. animalis , an increase in LPR was observed: in T47D cells by 4.3 times, in MCF-7 by 4.2 times, and in MDA-MB-231 cells by 2.7 times compared to intact cells (Fig. 3 b). The changes in the metabolic profile of B. animalis -treated BC cells also affected the activity of important glycolytic enzymes – LDH and G6PD. It was found that co-cultivation of T47D and MCF-7 cells with B. animalis was accompanied by a statistically significant increase in LDH activity by 88.7% and 32%, respectively, compared to the intact control. In MDA-MB-231 cells treated with B. animalis , the studied indicator did not change significantly (Fig. 3 c). In MCF-7 and MDA-MB-231 cells after their exposure to B. animalis , a statistically significant decrease in G6PD activity was observed compared to the intact cells. In particular, in MCF-7 cells, G6PD activity decreased by 2 times, while in MDA-MB-231 cells - by 7.5 times. In T47D cells treated with B. animalis , an increase in G6PD activity was observed by 1.7 times compared to control cells (Fig. 3 d). It was established that in B. animalis -treated BC cells a multidirectional change in the expression of the glucose transporter gene GLUT1 was observed (Fig. 4 a). It was shown that in cells of luminal subtype T47D, MCF-7 its levels increased by 188.96 (p = 0.042) and 7.13 (p = 0.034) times, while in cells of the basal subtype MDA-MB-231 similar indicator decreased by 1.98 times (p = 0.026). The diversity of the cell’s response to B. animalis was also shown by GLUT4 gene expression, which plays an important role in glucose uptake in BC cells. Co-cultivation of MCF-7 and MDA-MB-231 cells with B. animalis resulted in a statistically significant increase in GLUT4 expression by 2.3- and 7-fold, respectively. It is important to note that in B. animalis -treated T47D cells, a decrease in GLUT4 mRNA expression was observed (Fig. 4 b). It was proven that exposition BC cells of the luminal subtype by B. animalis caused an increase in mRNA expression of the LDH isotype A and LDH isotype B genes by 2.19 (p = 0.038) and 6.20 (p = 0.034) times for the T47D line and 2.64 (p = 0.033) and 8.40 (p = 0.027) times for the MCF-7 line, respectively (Fig. 5 ). At the same time, it was found that the influence of B. animalis was accompanied by an increase in the expression of the mRNA of the G6PD gene by 8.33 (p = 0.017) times in T47D cells; while for triple-negative MDA-MB-231 cells under bacterial influence, a decrease in the expression of this gene by 1.72 (p = 0.049) times was observed compared to the intact control (Fig. 6 ). One of the powerful regulators of glycolysis in tumor cells is ROS, which affect the activity of key metabolic enzymes or oxidize oncogenes or tumor suppressors [ 15 ]. ROS production was determined in intact and treated B. animalis BC cells. It was shown that in T47D and MCF-7 cells, this indicator statistically significant increases by 1.4 and 2.2 times compared to control cells, respectively. The greatest changes in ROS production were observed in B. animalis -treated MDA-MB-231 cells - increased by 4.1 times compared to intact cells (Fig. 7 ). The detected changes in the metabolic phenotype of BC cells indicate a significant modification of the biology of malignant cells not only at the biochemical level, but also at the level of mRNA expression of various signaling and regulatory genes. It is clear that under such conditions B. animalis can also affect the expression of cytoskeletal proteins (vimentin) and cell adhesion (E-cadherin, β-catenin), which are among the most widely known biomarkers of the EMT process. In T47D cells treated with B. animalis , increased vimentin expression was observed. In B. animalis- treated MCF-7 cells, vimentin and E-cadherin expression were downregulated by 63% and 55%, respectively, compared to intact cells. A decrease in E-cadherin (by 70%) and β-catenin (by 20%) expression relative to control was observed in MDA-MB-231 cells after exposure to B. animalis (Table 5 ). Table 5 Expression of EMT-associated proteins in intact and B. animalis -treated BC cells Cells Proteins expression, H-score system, points Vimentin Е-cadherin β-catenin T47D ≤ 10,0 ± 5,0 270,0 ± 20,0 250,0 ± 12,0 T47D + B. animalis 50,0 ± 3,5* 250,0 ± 15,0 240,0 ± 10,0 MCF-7 110,0 ± 10,0 90,0 ± 20,0 110,0 ± 15,0 MCF-7 + B. animalis 40,0 ± 5,0* 40,0 ± 2,0* 90,0 ± 10,0 MDA-MB-231 70,0 ± 7,0 85,0 ± 15,0 220,0 ± 10,0 MDA-MB-231 + B. animalis 55,0 ± 10,5 25,0 ± 2,5* 175,0 ± 5,5* * - p < 0.05 statistically significant difference compared to intact cells. Discussion The metabolic activity of tumor cells, particularly BC cells, is one of the key regulators of their survival, proliferation, invasion, metastasis, and sensitivity to chemotherapy [16]. Glycolysis is a critical catabolic process of glucose biotransformation and one of the main metabolic characteristics of malignant cells [17]. Therefore, any factors that can affect the glycolytic pathway of glucose metabolism in BC cells can significantly modify their viability and biological properties. The tumor microenvironment is an influential modifier of the malignant cells metabolism [16]. The tumor microbiome is considered an integral part of the tumor microenvironment. The complex relationship between the tumor and the microbiota affects the biology of tumor cells through the regulation of oncogenic pathways, modulation of the immune response, and interaction with secretory metabolites of microorganisms [18]. Bifidobacterium are a member of the human microflora [19] and in BC these microorganisms demonstrate their multifaceted effect, modifying various immunomodulatory and inflammatory signaling pathways, which potentially leads to inhibition of tumor growth [20]. In addition, it is known that different species of bifidobacteria are able to regulate the activity of signaling molecules that stimulate apoptosis [21, 22]. Although the diverse effects of bifidobacteria in the tumor microenvironment have been established, the specific mechanisms underlying their efficacy remain poorly understood. Therefore, determining the role of B. animalis as a modulator of some biological properties of BC cells of different molecular subtypes remains a relevant topic for research. According to obtained results, exposure of BC cells to B. animalis lead to a significant decrease in the number of viable cells, especially of the luminal subtype. At the same time, predominantly antiproliferative, rather than proapoptotic, effect of bifidobacteria on the cancer cells was shown. Our results confirmed the modification of the metabolic phenotype of all B. animalis -treated BC cells towards increased glycolysis. A statistically significant increase in GCR, LPR and LDH activity was observed in B. animalis -treated BC cells of all three lines. Meanwhile, the most sensitive to the influence of bifidobacteria were BC cells of the luminal subtype. A significant increase in mRNA expression of LDHA gene in luminal subtype BC cells treated with B. animalis confirms the enhancement of glycolysis, since it is this LDH isoform that ensures the conversion of pyruvate to lactate, regenerating NAD + to support this process [23]. The increase in mRNA expression of LDHВ gene in T47D and MCF-7 cells after their exposure to B. animalis may be a consequence of metabolic adaptation in oxidative cells, ensuring the reduction of NAD + to NADH + [24]. At the same time, the results of the mRNA analysis of the glucose transporter genes GLUT1 and GLUT4 expression in BC cells indicate that B. animalis enhances glucose uptake by these cells in different ways. In T47D cells, due to increased expression of the main glucose transporter GLUT1, which is responsible for the basal transport of monosaccharide [25]. In MCF-7 cells, by enhancing the expression of not only GLUT1 but also GLUT4 , which is activated and the response to specific inducers, e.g., insulin [26]. In MDA-MB-231 cells due to suppression of GLUT1 expression against the background of increased GLUT4 level. Overall, such changes in glucose transporter mRNA expression confirm the enhancement of glycolysis in BC cells after their co-cultivation with B. animalis [27] . The analysis of the redox system state of the studied cells revealed the greatest increase in the ROS concentration in B. animalis -treated basal subtype MDA-MB-231 cells (more than 4 times compared to intact cells). In the studied cells, G6PD activity correlates with the level of ROS production in a feedback loop. The greatest ROS increase was observed in cells with reduced activity of this enzyme, which may be a consequence of its depletion as a result of excessive use to stabilize the redox homeostasis of MDA-MB-231 and MCF-7 cells, which was disrupted by B. animalis treatment. Such changes in enzyme activity may also be a consequence of the switching of cell metabolism from PPP to glycolysis [28]. The described changes in G6PD activity correlate with changes in the expression level of the corresponding mRNA in the studied cells. Increased intracellular ROS/RNS activates G6PD mRNA expression, functioning as a defensive, stress-response mechanism [29]. Decreased G6PD activity is likely one of the mechanisms associated with decreased proliferation of BC cells, as enzyme deficiency in tumor cells is accompanied by changes in the expression of cell cycle regulatory proteins [30]. The obtained results confirm that B. animalis -treated BC cells are characterized by a shift in the metabolic profile towards increased glycolysis, inhibition of proliferation and induction of oxidative stress in cells. The most significant changes are experienced by the metabolic activity of luminal subtype BC cells, and the greatest increase in ROS production was found in basal subtype cells . The study of β-catenin, which is associated with the cadherin system and its appearance in the nucleus indicates that cells acquire the ability to invasion and migration, since the cytoplasmic domain of cadherins binds to β-catenin and p120, which are mediators of the actin cytoskeleton, showed a decrease in the expression of the marker in MDA-MB-231 cells, while in cells with a dominant epithelial phenotype, no changes in the expression of this biomarker were observed. Vimentin levels, a cytoskeletal protein whose expression is characteristic of cells of the mesenchymal phenotype, did not undergo statistically significant changes in BC cells of the high-grade phenotype - MDA-MB-231 under the influence of bacteria, while in T47D cells, induction of the expression of this biomarker was noted under the conditions of exposure to bacteria. Both the number of vimentin-positive cells and the intensity in T47D cells were low, but compared to the negative control - statistically significant. Today it is known that cadherins are transmembrane glycoproteins that support Ca2+-dependent intercellular adhesion bonds and play one of the most important roles in EMT. It is known that the loss or decrease in the expression of E-cadherin plays a significant role in the development of EMT, which is associated, among other things, with a change in a whole group of transcriptional repressors (Zeb-1, Zeb-2, Twist, Snail, Slug) [31, 32]. It was shown that the bacteria caused a statistically significant decrease in the number of cells expressing and the level of E-cadherin expression in high malignant breast cancer cells - MDA-MB-231. While the changes in E-cadherin expression in T47D cells were not significant and statistically insignificant under the conditions of exposure to B. animalis . Therefore, B. animalis causes a diverse effect on the expression of markers that characterize the EMT profile of BC cells depending on their their malignancy level of , which also indicates the modulation of cellular plasticity under the conditions of their exposure to microbiota components and requires further study of this phenomenon, since such modulation of plasticity will contribute not only to changing the metastatic characteristics of tumor cells, but also to changing their sensitivity to antitumor agents of different nature and mechanism of action. Thus, monitoring and identifying changes in the phenotypic and metabolic characteristics of tumor cells under the influence of modulators of various nature will contribute to the regulation of the behavior of a malignantly transformed cell and, accordingly, its response to antitumor agents. Conclusion In summary, it can be stated that Bifidobacterium animalis does not simply modulate individual metabolic or signaling pathways, but triggers a complex reprogramming of BC cells in a direction characteristic of their molecular subtype. For receptor-positive lines, proactive metabolic activation dominates with a possible increase in proliferative potential. In contrast, triple-negative cells showed a response more similar to adaptive, with signs of metabolic imbalance and rearrangement of growth regulatory cascades. Such differences suggest that the impact of microbiome components on tumor cells may be context-dependent and determined by receptor status, intrinsic metabolic configuration, and the ability of cells to integrate environmental signals. The data support the concept that bacteria can act as modulators of the tumor microenvironment and metabolic plasticity of breast cancer, and open prospects for further study of bacterial metabolites as potential regulators of tumor growth, their metastatic properties, and response to therapy. Declarations Funding This study was also performed within the framework of the research project “Study of Lactobacilli, Bifidobacteria and Opportunistic Pathogens of the Human Microbiota Influence on the Features of Mechanisms Realization of Metabolic Disturbances in the Tumor Process” (state registration No. 0121U113840) funded by the National Academy of Sciences of Ukraine. Clinical trial number : not applicable Ethics, Consent to Participate, and Consent to Publish declarations : not applicable. The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request. References Schiliro C, Firestein BL. 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Reactive Oxygen Species, Metabolic Plasticity, and Drug Resistance in Cancer. Int J Mol Sci. 2020; 21(10):3412. doi: 10.3390/ijms21103412 Zhao J, Jin D, Huang M, Ji J, Xu X, Wang F, Zhou L, Bao B, Jiang F, Xu W, Lu X, Xiao M. Glycolysis in the tumor microenvironment: a driver of cancer progression and a promising therapeutic target. Front Cell Dev Biol. 2024; 12:1416472. doi: 10.3389/fcell.2024.1416472 Yu L, Chen X, Wang L, Chen S. The sweet trap in tumors: aerobic glycolysis and potential targets for therapy. Oncotarget. 2016; 7(25):38908-38926. doi: 10.18632/oncotarget.7676 Ciernikova S, Sevcikova A, Stevurkova V, Mego M. Tumor microbiome - an integral part of the tumor microenvironment. Front Oncol. 2022; 12:1063100. doi: 10.3389/fonc.2022.1063100. Bottacini F, van Sinderen D, Ventura M. Omics of bifidobacteria: Research and insights into their health-promoting activities. 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Lactate dehydrogenase a is a crucial biomarker that affects the prognosis, chemotherapy effect, and immune infiltration of breast cancer. BMC Womens Health. 2025; 25(1):497. doi: 10.1186/s12905-025-04039-w Taha, M., Saad, K., El-Zeki, H. et al . L lactate dehydrogenase drives cancer metabolism and offers new therapeutic opportunities. Discov Appl Sci 2026; 8, 307. https://doi.org/10.1007/s42452-025-08114-7 Barbosa AM, Martel F. Targeting Glucose Transporters for Breast Cancer Therapy: The Effect of Natural and Synthetic Compounds. Cancers (Basel). 2020; 12(1):154. doi: 10.3390/cancers12010154 Shin E, Koo JS. Glucose Metabolism and Glucose Transporters in Breast Cancer. Front Cell Dev Biol. 2021; 9:728759. doi: 10.3389/fcell.2021.728759 Garrido P, Osorio FG, Morán J, Cabello E, Alonso A, Freije JM, González C. Loss of GLUT4 induces metabolic reprogramming and impairs viability of breast cancer cells. J Cell Physiol. 2015; 230(1):191-8. doi: 10.1002/jcp.24698. PMID: 24931902. Li Z., Zhang B., Yao W., Zhang C., Wan L., Zhang Y. APC-Cdh1 Regulates Neuronal Apoptosis Through Modulating Glycolysis and Pentose-Phosphate Pathway After Oxygen-Glucose Deprivation and Reperfusion. Cell Mol. Neurobiol. 2019; 39:123–135. doi: 10.1007/s10571-018-0638-x Ju, HQ., Lu, YX., Wu, QN. et al. Disrupting G6PD-mediated Redox homeostasis enhances chemosensitivity in colorectal cancer. Oncogene 2017; 36, 6282–6292. https://doi.org/10.1038/onc.2017.227 Yang HC, Wu YH, Yen WC, Liu HY, Hwang TL, Stern A, Chiu DT. The Redox Role of G6PD in Cell Growth, Cell Death, and Cancer. Cells. 2019; 8(9):1055. doi: 10.3390/cells8091055. Baranwal S, Alahari SK. Molecular mechanisms controlling E-cadherin expression in breast cancer. Biochem Biophys Res Commun. 2009; 384(1):6-11. doi: 10.1016/j.bbrc.2009.04.051. Kaszak I, Witkowska-Piłaszewicz O, Niewiadomska Z, Dworecka-Kaszak B, Ngosa Toka F, Jurka P. Role of Cadherins in Cancer-A Review. Int J Mol Sci. 2020; 21(20):7624. doi: 10.3390/ijms21207624. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 18 May, 2026 Reviews received at journal 13 May, 2026 Reviewers agreed at journal 07 May, 2026 Reviewers agreed at journal 07 May, 2026 Reviewers agreed at journal 07 May, 2026 Reviewers agreed at journal 06 May, 2026 Reviewers invited by journal 04 May, 2026 Editor assigned by journal 04 May, 2026 Editor invited by journal 04 May, 2026 Submission checks completed at journal 01 May, 2026 First submitted to journal 01 May, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9441737","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":638373823,"identity":"3cc65371-0059-4c2f-8c8d-ea0e6af25695","order_by":0,"name":"Petro Virych","email":"","orcid":"","institution":"R.E. Kavetsky Institute of Experimental Pathology, Oncology and Radiobiology, NAS of Ukraine","correspondingAuthor":false,"prefix":"","firstName":"Petro","middleName":"","lastName":"Virych","suffix":""},{"id":638373824,"identity":"67f136ca-20af-4392-b807-73e4cef81c94","order_by":1,"name":"Natalia Bezdieniezhnykh","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA4ElEQVRIiWNgGAWjYBACAzBZIAEkmA8ACQkZIrUYgLSwJYC08BCrBUTwQEiCWszZ2589+GFgIW/O3vP51Y0aCx4G9sNHN+DTYtlzIN2wx0DCcGfP2W3WOceADuNJS7uB12E3EoDKDCQYN9zI3WacwwbUIsFjhl/L/Ydtkn8MJOw33Mh5ZpzzjxgtN5jZpIG2JAK1MD/ObSNCi2VPGpu0jIFE8oYzx8yYc/skeNgI+cWc/fgzyTcVdbYbjjc//pzzrU6On/3wMbxakAGbBJgkVjkIMH8gRfUoGAWjYBSMHAAAQIxEE2/xPmMAAAAASUVORK5CYII=","orcid":"","institution":"R.E. Kavetsky Institute of Experimental Pathology, Oncology and Radiobiology, NAS of Ukraine","correspondingAuthor":true,"prefix":"","firstName":"Natalia","middleName":"","lastName":"Bezdieniezhnykh","suffix":""},{"id":638373825,"identity":"525ed0b0-ccd8-4fc6-937d-4cbfdea82b31","order_by":2,"name":"Oleksandra Lykhova","email":"","orcid":"","institution":"R.E. Kavetsky Institute of Experimental Pathology, Oncology and Radiobiology, NAS of Ukraine","correspondingAuthor":false,"prefix":"","firstName":"Oleksandra","middleName":"","lastName":"Lykhova","suffix":""},{"id":638373826,"identity":"7c95cc61-f9ba-4a5e-8c04-b7870a1866b8","order_by":3,"name":"Oleksandr Mushii","email":"","orcid":"","institution":"R.E. Kavetsky Institute of Experimental Pathology, Oncology and Radiobiology, NAS of Ukraine","correspondingAuthor":false,"prefix":"","firstName":"Oleksandr","middleName":"","lastName":"Mushii","suffix":""},{"id":638373827,"identity":"0c83ecf9-a405-46ab-9ed3-a1f451fa910b","order_by":4,"name":"Tamara Kozak","email":"","orcid":"","institution":"R.E. Kavetsky Institute of Experimental Pathology, Oncology and Radiobiology, NAS of Ukraine","correspondingAuthor":false,"prefix":"","firstName":"Tamara","middleName":"","lastName":"Kozak","suffix":""},{"id":638373828,"identity":"eb322d40-20f2-4059-8823-483c973cc532","order_by":5,"name":"Vasyl Chekhun","email":"","orcid":"","institution":"R.E. Kavetsky Institute of Experimental Pathology, Oncology and Radiobiology, NAS of Ukraine","correspondingAuthor":false,"prefix":"","firstName":"Vasyl","middleName":"","lastName":"Chekhun","suffix":""}],"badges":[],"createdAt":"2026-04-16 19:53:36","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9441737/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9441737/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":109072540,"identity":"a70323f9-a784-46a5-88ed-67c7886294a5","added_by":"auto","created_at":"2026-05-12 10:43:01","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1381677,"visible":true,"origin":"","legend":"\u003cp\u003eViability of BC cells of different molecular subtypes after incubation with \u003cem\u003eB. animalis\u003c/em\u003e for 72 hours. The number of viable cells was determined by the trypan blue test. BA - \u003cem\u003eBifidobacterium animalis.\u003c/em\u003e * - p \u0026lt; 0.05 statistically significant difference compared to intact cells.\u003c/p\u003e","description":"","filename":"Fig.1..png","url":"https://assets-eu.researchsquare.com/files/rs-9441737/v1/6674cb865e3f029dbfa3b335.png"},{"id":109072624,"identity":"7ac9d7b5-c36b-4329-99bf-50a17f4f3627","added_by":"auto","created_at":"2026-05-12 10:43:18","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1528358,"visible":true,"origin":"","legend":"\u003cp\u003ePercentage of the T47D (a), MCF-7 (b) and MDA-MB-231 (c) cells at different stages of apoptosis after incubation with \u003cem\u003eB. animalis\u003c/em\u003e for 72 hours: green - live cells, yelow - early apoptosis, orange - medium apoptosis, red - late apoptosis. Cell death rates were determined by flow cytometry in the Annexin V and propidium iodide assay.\u003c/p\u003e","description":"","filename":"Fig.2..png","url":"https://assets-eu.researchsquare.com/files/rs-9441737/v1/850ccc5b741f4b84a2f6fa78.png"},{"id":109072408,"identity":"81027314-6a5b-493f-8a68-7133fb8e9966","added_by":"auto","created_at":"2026-05-12 10:42:14","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":3544166,"visible":true,"origin":"","legend":"\u003cp\u003eChanges in the metabolic profile of BC cells of different molecular subtypes after incubation with \u003cem\u003eB. animalis\u003c/em\u003e for 72 hours. (a) – GCR, (b) – LPR, (c) – LDH activity, (d) – G6PD activity. * - p \u0026lt; 0.05 statistically significant difference compared to intact cells.\u003c/p\u003e","description":"","filename":"Fig.3..png","url":"https://assets-eu.researchsquare.com/files/rs-9441737/v1/1cf71c04427fa91ad895d52f.png"},{"id":109072544,"identity":"055129bc-b2e1-4fd0-937b-627d30e624ee","added_by":"auto","created_at":"2026-05-12 10:43:02","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":1783856,"visible":true,"origin":"","legend":"\u003cp\u003eChanges in mRNA expression of \u003cem\u003eGLUT1\u003c/em\u003e (a) and \u003cem\u003eGLUT4\u003c/em\u003e (b) genes in BC cell of different molecular subtypes after co-cultivation with \u003cem\u003eB. animalis \u003c/em\u003e(BA). * - p \u0026lt; 0.05 statistically significant difference compared to intact cells.\u003c/p\u003e","description":"","filename":"Fig.4..png","url":"https://assets-eu.researchsquare.com/files/rs-9441737/v1/1c6347d910bb2ed3aceda630.png"},{"id":109072409,"identity":"08387f14-dbe7-4314-a65e-d91badf71140","added_by":"auto","created_at":"2026-05-12 10:42:14","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":1640751,"visible":true,"origin":"","legend":"\u003cp\u003eChanges in mRNA expression of \u003cem\u003eLDHA \u003c/em\u003e(a) and \u003cem\u003eLDHB\u003c/em\u003e (b) genes in BC cell lines of differentmolecular subtypes under the influence of \u003cem\u003eB. animalis \u003c/em\u003e(BA). * - p \u0026lt; 0.05 statistically significant difference compared to intact cells.\u003c/p\u003e","description":"","filename":"Fig.5..png","url":"https://assets-eu.researchsquare.com/files/rs-9441737/v1/82a042aa15bc5ede9bec3236.png"},{"id":109072623,"identity":"93844e4c-6200-4829-8fbc-736f4b58c6ca","added_by":"auto","created_at":"2026-05-12 10:43:17","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":894670,"visible":true,"origin":"","legend":"\u003cp\u003eChanges in \u003cem\u003eG6PD\u003c/em\u003e mRNA expression in BC cells of different molecular subtypesunder the influence of \u003cem\u003eB. animalis \u003c/em\u003e(BA). * - p \u0026lt; 0.05 statistically significant difference compared to intact cells.\u003c/p\u003e","description":"","filename":"Fig.6..png","url":"https://assets-eu.researchsquare.com/files/rs-9441737/v1/691ffc936ae7639baaad1b13.png"},{"id":109072543,"identity":"43782c11-5f04-4161-82d1-8e66e80127f4","added_by":"auto","created_at":"2026-05-12 10:43:02","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":875637,"visible":true,"origin":"","legend":"\u003cp\u003eRelative ROS concentration in BC cells of different molecular subtypes after incubation with \u003cem\u003eB. animalis\u003c/em\u003e (BA) for 72 hours. * - p \u0026lt; 0.05 statistically significant difference compared to intact cells.\u003c/p\u003e","description":"","filename":"Fig.7..png","url":"https://assets-eu.researchsquare.com/files/rs-9441737/v1/6be46e7d38b496716fa44b99.png"},{"id":109204552,"identity":"413a2b34-ca40-4fb8-b809-449b601d73a7","added_by":"auto","created_at":"2026-05-13 15:01:03","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":11917731,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9441737/v1/94696b0b-dc5e-40e7-a293-e5d71a8b06fd.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003eModulation of the Molecular Biological Profile of Breast Cancer Cells by Exposure to Bifidobacterium Аnimalis\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eCharacteristics typical of cells with a malignant phenotype include unlimited capacity for replication, evasion of apoptosis, insensitivity to growth-inhibiting signals, tissue invasion, and metastasis. In order for malignant cells to obtain the energy and materials necessary to maintain these characteristics, they must undergo reprogramming of their metabolic pathways [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. This reprogramming results in increased glucose uptake, lactate accumulation, lipid metabolism disorders, and other changes, which is an adaptive process necessary for cell expansion and persistent signals for proliferation to meet the survival needs of tumor cells in specific microenvironments [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. The key driver in the spread of tumor cells and their adaptation to a new microenvironment, i.e. their acquisition of a metastatic phenotype, is the process of epithelial-mesenchymal transition [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. The EMT program is activated by a number of signals, in particular, the influence of growth factors, various cytokines, primarily of stromal origin. During a malignant process, the system of signaling cascades initiated in the system of the tumor microenvironment is unbalanced, which stimulates the progression of the disease [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Metastatic cells adjust their metabolism accordingly to adapt, and part of the genetic reprogramming orchestrated by EMT affects the expression of metabolic genes, regulating glucose, lipid, glutamine, and nucleotide metabolism. However, the extent of this reprogramming of the metabolic network remains unclear. Further questions about the relationship between EMT and the altered metabolic profile of tumor cells have been raised by the discovery that oncogenic mutations in certain metabolic enzymes (fumarate hydratase, succinate dehydrogenase, and isocitrate dehydrogenase), drive EMT [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. At the same time, according to the authors, it is shown that tumor cells with a dominant mesenchymal phenotype have different metabolic needs compared to their epithelial counterparts to meet the metabolic needs of increased motility and invasion. Thus, according to Shaul and colleagues, mesenchymal cells demonstrate high levels of expression of 44 metabolic genes. It was found that these genes are also upregulated upon induction of EMT by expression of Twist1 in human mammary epithelial cells [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. However, the mechanism of such regulation is currently unknown.\u003c/p\u003e \u003cp\u003eAccording to known data and our previous studies, certain members of probiotic strains, namely \u003cem\u003eBifidobacterium\u003c/em\u003e, may act as modifiers of the metabolism of tumor cells in general and breast cancer (BC) cells in particular. It has been shown that co-cultivation of BC cells with \u003cem\u003eBifidobacterium animalis\u003c/em\u003e is accompanied by changes in the processes of glucose metabolism in malignant cells, in particular, increased glycolysis [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Such facts open up the following questions and the formation of the next stages for studying the role of certain components of the microenvironment, which already includes the microbiome, as a regulator of both the metabolic profile and the metastatic phenotype of malignantly transformed cells. Therefore, in this manuscript, we will consider the effect of co-cultivation of \u003cem\u003eBifidobacterium animalis\u003c/em\u003e with BC cells on the modification of metabolic and phenotypic characteristics of tumor cells, in particular those associated with their malignant properties.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cp\u003e \u003cem\u003eCells.\u003c/em\u003e Human BC cells of T47D, MCF-7 (luminal subtype) and MDA-MB-231 (basal subtype) cell lines were obtained from the Bank of Cell Lines from Human and Animal Tissues of the R.E. Kavetsky Institute of Experimental Pathology, Oncology and Radiobiology of the NAS of Ukraine (Registration Certificate, series AN No. 41 dated 19.02.2009). BC cells were cultured in DMEM culture medium containing 4 mmol/L L-glutamine (BioWest, France), 10% fetal bovine serum (FBS) (BioWest, France) and 1x penicillin-streptomycin (BioWest, France). Cells were incubated at 37\u0026deg;C in a humidified atmosphere supplied with 5% CO\u003csub\u003e2\u003c/sub\u003e. The medium changing and cell passaging were performed according to standard procedures [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Cells were passaged after they reached 80% \u0026minus;\u0026thinsp;90% confluency using Versene's solution (Vetline Agroscience, Ukraine) and Trypsin \u0026ndash; EDTA 1X in PBS (BioWest, France). Cells in exponential growth phase were used in the experiments.\u003c/p\u003e \u003cp\u003e \u003cem\u003eBacteria.\u003c/em\u003e Live lyophilized cells of \u003cem\u003eBifidobacterium animalis subsp. lactis\u003c/em\u003e BB-12 isolated from a probiotic produced by Lek Pharmaceuticals, Ljubljana, Slovenia (Linex Baby, Sandoz, PT1042), were used in the study. Bacterial cells were diluted in DMEM without antibiotic.\u003c/p\u003e \u003cp\u003e \u003cem\u003eCo-cultivation of BC cells and live B. animalis under the condition of their direct interaction.\u003c/em\u003e BC cells were seeded in 75 cm\u003csup\u003e2\u003c/sup\u003e plastic flasks at a number of 1x10\u003csup\u003e6\u003c/sup\u003e. Cells were planted in DMEM with 10% FBS without antibiotic. Cells were incubated at 37\u0026deg;C in a humidified atmosphere with 5% CO\u003csub\u003e2\u003c/sub\u003e for 10 hours, after which the medium was completely changed and bacteria were added in a ratio of eukaryotic/bacterial cells of 1/400. Cells were incubated at 37\u0026deg;C and 5% CO\u003csub\u003e2\u003c/sub\u003e for 72 hours. BC cells, which were cultured under standard conditions without bacteria, were used as a control for eukaryotic cells.\u003c/p\u003e \u003cp\u003eThe medium after incubation was collected for further measurement of glucose and lactate concentrations. The number of live BC cells was determined by trypan blue assay (Appliсhem, Germany), the cells were lysed in RIPA buffer [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e] supplemented with protease inhibitor cocktail (Sigma-Aldrich, USA) and used to measure the activities of intracellular lactate dehydrogenase (LDH) and glucose-6-phosphate dehydrogenase (G6PD).\u003c/p\u003e \u003cp\u003e \u003cem\u003eDetermination of glucose consumption rate and lactate production rate.\u003c/em\u003e The studied parameters were determined using the automatic analyzer GBG ChemWell 2900 (Awareness Technology, USA). To determine the glucose concentration, a colorimetric enzymatic method with glucose oxidase was used, and to determine the lactate concentration, an enzymatic method using lactate oxidase was used. The determination was performed using the diagnostic kits \u0026ldquo;Glucose (Ox) Liquid\u0026rdquo; (MedTest Dx, Pointe Scientific, USA) and \u0026ldquo;Lactate\u0026rdquo; (Greiner Diagnostic GmbH, Germany) according to the manufacturer\u0026rsquo;s instructions.\u003c/p\u003e \u003cp\u003eThe glucose metabolism indicators of BC cells \u0026ndash; the rate of glucose consumption (GCR) and lactate production (LPR) \u0026ndash; were determined using the formulas [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]:\u003cdiv id=\"Equa\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e\n$$\\:GCR=2\\times\\:\\frac{\\left({C}_{gl}\\left({t}_{i}\\right)-{C}_{gl}\\left({t}_{i+1}\\right)\\right)\\times\\:V}{N\\left({t}_{i}\\right)+N\\left({t}_{i+1}\\right)}$$\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Equb\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equb\" name=\"EquationSource\"\u003e\n$$\\:LPR=2\\times\\:\\frac{\\left({C}_{L}\\left({t}_{i+1}\\right)-{C}_{L}\\left({t}_{i}\\right)\\right)\\times\\:V}{N\\left({t}_{i}\\right)+N\\left({t}_{i+1}\\right)}$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003ewhere concentrations of glucose and lactate at two consecutive days (\u003cem\u003et\u003c/em\u003e\u003csub\u003e\u003cem\u003ei\u003c/em\u003e\u003c/sub\u003e and \u003cem\u003et\u003c/em\u003e\u003csub\u003e\u003cem\u003ei+1\u003c/em\u003e\u003c/sub\u003e) of cell growth are marked as \u003cem\u003eC\u003c/em\u003e\u003csub\u003e\u003cem\u003egl\u003c/em\u003e\u003c/sub\u003e\u003cem\u003e(t\u003c/em\u003e\u003csub\u003e\u003cem\u003ei+1\u003c/em\u003e\u003c/sub\u003e\u003cem\u003e), C\u003c/em\u003e\u003csub\u003e\u003cem\u003eL\u003c/em\u003e\u003c/sub\u003e\u003cem\u003e(t\u003c/em\u003e\u003csub\u003e\u003cem\u003ei\u003c/em\u003e\u003c/sub\u003e\u003cem\u003e), C\u003c/em\u003e\u003csub\u003e\u003cem\u003eL\u003c/em\u003e\u003c/sub\u003e\u003cem\u003e(t\u003c/em\u003e\u003csub\u003e\u003cem\u003ei+1\u003c/em\u003e\u003c/sub\u003e\u003cem\u003e); N(t\u003c/em\u003e\u003csub\u003e\u003cem\u003ei\u003c/em\u003e\u003c/sub\u003e\u003cem\u003e)\u003c/em\u003e, and \u003cem\u003eN(t\u003c/em\u003e\u003csub\u003e\u003cem\u003ei+1\u003c/em\u003e\u003c/sub\u003e\u003cem\u003e)\u003c/em\u003e are the counts of ВC cells on corresponding consecutive days of growth; \u003cem\u003eV\u003c/em\u003e is the volume of the incubation medium per well.\u003c/p\u003e \u003cp\u003e \u003cem\u003eMeasurement of intracellular LDH and G6PD activities.\u003c/em\u003e Enzyme activities were measured in BC cells lysates. The resulting lysates were centrifuged in a high-speed refrigerated centrifuge (Sigma, USA) at 13,000 rpm and 4\u0026deg;C for 15 min. The collected supernatant was used to analyze the enzyme activities. A kinetic method using L-lactate from a Lactate Dehydrogenase Set (Pointe Scientific, USA) and glucose-6-phosphate from a Glucose-6-Phosphate Dehydrogenase Set (MedTest Dx, Pointe Scientific, USA) was used. Both analyses were performed according to the manufacturer\u0026rsquo;s instructions. The enzyme activities were calculated based on the number of cells in each sample.\u003c/p\u003e \u003cp\u003e \u003cem\u003eDetermination of BC cell death indices.\u003c/em\u003e The percentage of viable, apoptotic and necrotic cells was determined using Annexin V conjugated to the fluorescent dye FITC and propidium iodide (PI) using the Annexin V - FITC Apoptosis Detection Kit (Dojindo, Japan). BC cells were detached from the substrate with trypsin solution (Biowest, France), washed three times with PBS and stained according to the kit manufacturer\u0026rsquo;s protocol. Results were obtained using a DxFlex flow cytometer (Beckman Coulter) equipped with a 488 nm blue laser. Annexin V-FITC staining was analyzed in the FITC channel, and PI staining was analyzed in the ECD channel. Apoptosis/necrosis parameters were assessed using a four-quadrant gate on a FITC-A/ECD-A dot matrix with gate position adjustment for samples stained with either annexin or PI alone. At least 10,000 events were analyzed for each sample. Data analysis was performed using CytExpert for DxFlex software.\u003c/p\u003e \u003cp\u003e \u003cem\u003eImmunocytochemical analysis.\u003c/em\u003e Coverslips with BC cells, following incubation with \u003cem\u003eB. animalis\u003c/em\u003e were fixed with a 1:1 solution of methanol (Merck, Germany) and acetone (Khimrezerv, Ukraine) for 2 hours at -20\u0026deg;C and then washed three times with cold PBS (BioWest, France). The immunocytochemical reaction was performed using a Master Polymer Plus Detection System (Peroxidase) kit (Vitro SA, Spain). The reaction was carried out according to the manufacturer's instructions. The coverslips were covered with Vimentin, E-cadherin and β-catenin primary antibodies (Vitro SA, Spain) and left to incubate for 1 hour at room temperature. After the reaction, the coverslips were stained with hematoxylin and eosin solution (Sigma, USA) and fixed in Faramount Aqueous Mounting Medium (Thermo Fisher Scientific, USA). The resulting preparations were analyzed by counting cells with expression (brown), taking into account the color intensity, using a Axiostar Plus light microscope (Carl Zeiss, Germany) at x400 magnification, and photographed with a digital camera (Canon PowerShot G5, UK) at a x1000 magnification. At least three random fields of view were analyzed. Expression was assessed using the H-Score [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003cem\u003eReal-time reverse transcription PCR.\u003c/em\u003e The total RNA pool from human BC cells was isolated using the commercial \u0026ldquo;RNeasy Plus Mini Kit\u0026rdquo; (QIAGEN, Germany) according to the manufacturer\u0026rsquo;s protocol. The amount of isolated RNA was determined on a \u0026ldquo;NanoDrop 2000c Spectrophotometer\u0026rdquo; (ThermoScientific, USA). To study mRNA expression, cDNA was synthesized from 100ng of total RNA using the LunaScript\u0026reg; RT SuperMix Kit (New England Biolabs, Inc., USA) for reverse transcription.\u003c/p\u003e \u003cp\u003eThe primer sequences for mRNA detection of the studied genes were obtained using the resource \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.ncbi.nlm.nih.gov/tools/primer-blast\u003c/span\u003e\u003cspan address=\"https://www.ncbi.nlm.nih.gov/tools/primer-blast\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e and synthesized by Metabion, Germany (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). A quantitative real-time PCR was performed on a QuantStudio 5 Dx Real-Time PCR System (Thermo Fisher Scientific, USA) using a LunaScript\u0026reg; MasterMix Kit (New England Biolabs, USA). β-actin mRNA was used as an endogenous control to determine mRNA expression.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePrimer sequences for mRNA expression\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGen\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003ePrimer\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003eGLUT1\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eForvard\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTTG CAG GCT TCT CCA ACT GGA C\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReverse\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCAG AAC CAG GAG CAC AGT GAA G\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003eGLUT4\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eForvard\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eACG AGG CTT CTT CTA CAC ACC C\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReverse\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTCC ACA ATG CCA CGC TTC TGC A\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003eG6PD\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eForvard\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCTG TTC CGT GAG GAC CAG ATC T\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReverse\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTGA AGG TGA GGA TAA CGC AGG C\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003eLDHA\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eForvard\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGGA TCT CCA ACA TGG CAG CCT T\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReverse\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAGA CGG CTT TCT CCC TCT TGC T\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003eLDHB\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eForvard\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGGA CAA GTT GGT ATG GCG TGT G\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReverse\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAAG CTC CCA TGC TGC AGA TCC A\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe threshold cycle was averaged across all replicates of each sample. Expression differences between the mRNAs tested relative to the control were calculated using the formula 2-\u003csup\u003eΔCt\u003c/sup\u003e. The error bars for the expression difference calculations show the range of ΔCt values based on including the standard deviation in these values ​​(ΔCt\u0026thinsp;=\u0026thinsp;Ct(mRNA of the test gene)-Ct(mRNA β-actin))\u003c/p\u003e \u003cp\u003e \u003cem\u003eStatistical analysis.\u003c/em\u003e The experiments were performed three times. The mean value of the studied indicators (M), standard deviation (SD) and Welch's t-test were calculated using the GraphGad Prism 8.0.1 software package. Differences were considered statistically significant at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eBC cells were treated with \u003cem\u003eB. animalis\u003c/em\u003e for 72 hours and the viability, redox status and metabolic profile of these cells were analyzed. The results obtained at this stage allowed us to assess the differences in the proliferative and glycolytic activity of the original and bifidobacteria-treated tumor cells of different molecular subtypes. In the trypan blue test, it was shown that \u003cem\u003eB. animalis\u003c/em\u003e causes a statistically significant decrease in the number of viable cells of the T47D line by 43%, MCF-7 by 52% and MDA-MB-231 by 26%, compared to control cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAt the same time, a comparative analysis of the percentage of apoptotic cells in the population of intact and \u003cem\u003eB. animalis\u003c/em\u003e-treated BC cells of all three lines did not reveal a statistically significant difference in the studied indicators (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe metabolic profile of BC cells after co-cultivation with \u003cem\u003eB. animalis\u003c/em\u003e was studied by analyzing a set of biochemical parameters associated with glycolysis. In particular, the GCR and LPR, the activity of LDH and G6FD. In T47D and MCF-7 cells of the luminal subtype treated with \u003cem\u003eB. animalis\u003c/em\u003e, GCR was statistically significantly increased by 2\u0026ndash;2.2 times, respectively, compared with intact cells. In basal subtype MDA-MB-231 cells treated with \u003cem\u003eB. animalis\u003c/em\u003e, an increase of this indicator by 1.8 times was also observed compared to control (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ea). Also, in BC cells of all three lines treated with \u003cem\u003eB. animalis\u003c/em\u003e, an increase in LPR was observed: in T47D cells by 4.3 times, in MCF-7 by 4.2 times, and in MDA-MB-231 cells by 2.7 times compared to intact cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eb).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe changes in the metabolic profile of \u003cem\u003eB. animalis\u003c/em\u003e-treated BC cells also affected the activity of important glycolytic enzymes \u0026ndash; LDH and G6PD. It was found that co-cultivation of T47D and MCF-7 cells with \u003cem\u003eB. animalis\u003c/em\u003e was accompanied by a statistically significant increase in LDH activity by 88.7% and 32%, respectively, compared to the intact control. In MDA-MB-231 cells treated with \u003cem\u003eB. animalis\u003c/em\u003e, the studied indicator did not change significantly (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ec).\u003c/p\u003e \u003cp\u003eIn MCF-7 and MDA-MB-231 cells after their exposure to \u003cem\u003eB. animalis\u003c/em\u003e, a statistically significant decrease in G6PD activity was observed compared to the intact cells. In particular, in MCF-7 cells, G6PD activity decreased by 2 times, while in MDA-MB-231 cells - by 7.5 times. In T47D cells treated with \u003cem\u003eB. animalis\u003c/em\u003e, an increase in G6PD activity was observed by 1.7 times compared to control cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ed).\u003c/p\u003e \u003cp\u003eIt was established that in \u003cem\u003eB. animalis\u003c/em\u003e-treated BC cells a multidirectional change in the expression of the glucose transporter gene \u003cem\u003eGLUT1\u003c/em\u003e was observed (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ea). It was shown that in cells of luminal subtype T47D, MCF-7 its levels increased by 188.96 (p\u0026thinsp;=\u0026thinsp;0.042) and 7.13 (p\u0026thinsp;=\u0026thinsp;0.034) times, while in cells of the basal subtype MDA-MB-231 similar indicator decreased by 1.98 times (p\u0026thinsp;=\u0026thinsp;0.026).\u003c/p\u003e \u003cp\u003eThe diversity of the cell\u0026rsquo;s response to \u003cem\u003eB. animalis\u003c/em\u003e was also shown by \u003cem\u003eGLUT4\u003c/em\u003e gene expression, which plays an important role in glucose uptake in BC cells. Co-cultivation of MCF-7 and MDA-MB-231 cells with \u003cem\u003eB. animalis\u003c/em\u003e resulted in a statistically significant increase in \u003cem\u003eGLUT4\u003c/em\u003e expression by 2.3- and 7-fold, respectively. It is important to note that in \u003cem\u003eB. animalis\u003c/em\u003e-treated T47D cells, a decrease in \u003cem\u003eGLUT4\u003c/em\u003e mRNA expression was observed (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eb).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eIt was proven that exposition BC cells of the luminal subtype by \u003cem\u003eB. animalis\u003c/em\u003e caused an increase in mRNA expression of the \u003cem\u003eLDH\u003c/em\u003e isotype A and \u003cem\u003eLDH\u003c/em\u003e isotype B genes by 2.19 (p\u0026thinsp;=\u0026thinsp;0.038) and 6.20 (p\u0026thinsp;=\u0026thinsp;0.034) times for the T47D line and 2.64 (p\u0026thinsp;=\u0026thinsp;0.033) and 8.40 (p\u0026thinsp;=\u0026thinsp;0.027) times for the MCF-7 line, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAt the same time, it was found that the influence of \u003cem\u003eB. animalis\u003c/em\u003e was accompanied by an increase in the expression of the mRNA of the \u003cem\u003eG6PD\u003c/em\u003e gene by 8.33 (p\u0026thinsp;=\u0026thinsp;0.017) times in T47D cells; while for triple-negative MDA-MB-231 cells under bacterial influence, a decrease in the expression of this gene by 1.72 (p\u0026thinsp;=\u0026thinsp;0.049) times was observed compared to the intact control (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eOne of the powerful regulators of glycolysis in tumor cells is ROS, which affect the activity of key metabolic enzymes or oxidize oncogenes or tumor suppressors [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. ROS production was determined in intact and treated \u003cem\u003eB. animalis\u003c/em\u003e BC cells. It was shown that in T47D and MCF-7 cells, this indicator statistically significant increases by 1.4 and 2.2 times compared to control cells, respectively. The greatest changes in ROS production were observed in \u003cem\u003eB. animalis\u003c/em\u003e-treated MDA-MB-231 cells - increased by 4.1 times compared to intact cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe detected changes in the metabolic phenotype of BC cells indicate a significant modification of the biology of malignant cells not only at the biochemical level, but also at the level of mRNA expression of various signaling and regulatory genes. It is clear that under such conditions \u003cem\u003eB. animalis\u003c/em\u003e can also affect the expression of cytoskeletal proteins (vimentin) and cell adhesion (E-cadherin, β-catenin), which are among the most widely known biomarkers of the EMT process.\u003c/p\u003e \u003cp\u003eIn T47D cells treated with \u003cem\u003eB. animalis\u003c/em\u003e, increased vimentin expression was observed. In \u003cem\u003eB. animalis-\u003c/em\u003etreated MCF-7 cells, vimentin and E-cadherin expression were downregulated by 63% and 55%, respectively, compared to intact cells. A decrease in E-cadherin (by 70%) and β-catenin (by 20%) expression relative to control was observed in MDA-MB-231 cells after exposure to \u003cem\u003eB. animalis\u003c/em\u003e (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eExpression of EMT-associated proteins in intact and \u003cem\u003eB. animalis\u003c/em\u003e-treated BC cells\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCells\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eProteins expression, H-score system, points\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eVimentin\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eЕ-cadherin\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eβ-catenin\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT47D\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e\u0026le;\u0026thinsp;10,0\u0026thinsp;\u0026plusmn;\u0026thinsp;5,0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e270,0\u0026thinsp;\u0026plusmn;\u0026thinsp;20,0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e250,0\u0026thinsp;\u0026plusmn;\u0026thinsp;12,0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT47D\u0026thinsp;+\u0026thinsp;\u003cem\u003eB. animalis\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e50,0\u0026thinsp;\u0026plusmn;\u0026thinsp;3,5*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e250,0\u0026thinsp;\u0026plusmn;\u0026thinsp;15,0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e240,0\u0026thinsp;\u0026plusmn;\u0026thinsp;10,0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMCF-7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e110,0\u0026thinsp;\u0026plusmn;\u0026thinsp;10,0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e90,0\u0026thinsp;\u0026plusmn;\u0026thinsp;20,0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e110,0\u0026thinsp;\u0026plusmn;\u0026thinsp;15,0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMCF-7\u0026thinsp;+\u0026thinsp;\u003cem\u003eB. animalis\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e40,0\u0026thinsp;\u0026plusmn;\u0026thinsp;5,0*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e40,0 \u0026plusmn; 2,0*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e90,0\u0026thinsp;\u0026plusmn;\u0026thinsp;10,0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMDA-MB-231\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e70,0\u0026thinsp;\u0026plusmn;\u0026thinsp;7,0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e85,0\u0026thinsp;\u0026plusmn;\u0026thinsp;15,0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e220,0\u0026thinsp;\u0026plusmn;\u0026thinsp;10,0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMDA-MB-231\u0026thinsp;+\u0026thinsp;\u003cem\u003eB. animalis\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e55,0 \u0026plusmn; 10,5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e25,0\u0026thinsp;\u0026plusmn;\u0026thinsp;2,5*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e175,0 \u0026plusmn; 5,5*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e* - p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 statistically significant difference compared to intact cells.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe metabolic activity of tumor cells, particularly BC cells, is one of the key regulators of their survival, proliferation, invasion, metastasis, and sensitivity to chemotherapy [16]. Glycolysis is a critical catabolic process of glucose biotransformation and one of the main metabolic characteristics of malignant cells [17]. Therefore, any factors that can affect the glycolytic pathway of glucose metabolism in\u0026nbsp;BC\u0026nbsp;cells can significantly modify their viability and biological properties.\u003c/p\u003e\n\u003cp\u003eThe tumor microenvironment is an influential modifier of the malignant cells metabolism [16]. The tumor microbiome is considered an integral part of the tumor microenvironment. The complex relationship between the tumor and the microbiota affects the biology of tumor cells through the regulation of oncogenic pathways, modulation of the immune response, and interaction with secretory metabolites of microorganisms [18]. \u003cem\u003eBifidobacterium\u003c/em\u003e are a member of the human microflora [19] and in BC these microorganisms demonstrate their multifaceted effect, modifying various immunomodulatory and inflammatory signaling pathways, which potentially leads to inhibition of tumor growth [20]. In addition, it\u0026nbsp;is known that different species of bifidobacteria are able to regulate the activity of signaling molecules that stimulate apoptosis [21, 22]. Although the diverse effects of bifidobacteria in the tumor microenvironment have been established, the specific mechanisms underlying their efficacy remain poorly understood. Therefore, determining the role of \u003cem\u003eB. animalis\u003c/em\u003e as a modulator of some biological properties of BC cells of different molecular subtypes remains a relevant topic for research.\u003c/p\u003e\n\u003cp\u003eAccording to obtained results, exposure of BC cells to \u003cem\u003eB. animalis\u003c/em\u003e lead to a significant decrease in the number of viable cells, especially of the luminal subtype. At the same time, \u0026nbsp;predominantly antiproliferative, rather than proapoptotic, effect of bifidobacteria on the cancer cells was shown.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOur\u0026nbsp;results confirmed the modification of the metabolic phenotype of all \u003cem\u003eB. animalis\u003c/em\u003e-treated BC cells towards increased glycolysis. A statistically significant increase in GCR, LPR and LDH activity was observed in \u003cem\u003eB. animalis\u003c/em\u003e-treated BC cells of all three lines. Meanwhile, the most sensitive to the influence of bifidobacteria were BC cells of the luminal subtype.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eA significant increase in mRNA expression of\u0026nbsp;\u003cem\u003eLDHA\u003c/em\u003e gene in luminal subtype\u0026nbsp;BC\u0026nbsp;cells treated with \u003cem\u003eB. animalis\u003c/em\u003e confirms the enhancement of glycolysis, since it is this LDH isoform that ensures the conversion of pyruvate to lactate, regenerating NAD\u003csup\u003e+\u003c/sup\u003e to support this process\u0026nbsp;[23]. The increase in mRNA expression\u0026nbsp;of\u0026nbsp;\u003cem\u003eLDHВ\u003c/em\u003e gene in T47D and MCF-7 cells after their exposure to \u003cem\u003eB. animalis\u003c/em\u003e may be a consequence of metabolic adaptation in oxidative cells, ensuring the reduction of NAD\u003csup\u003e+\u003c/sup\u003e to NADH\u003csup\u003e+\u0026nbsp;\u003c/sup\u003e[24].\u003c/p\u003e\n\u003cp\u003eAt the same time, the results of the mRNA analysis of the glucose transporter genes \u003cem\u003eGLUT1\u0026nbsp;\u003c/em\u003eand \u003cem\u003eGLUT4\u003c/em\u003e expression in BC cells indicate that \u003cem\u003eB. animalis\u003c/em\u003e enhances glucose uptake by these cells in different ways. In T47D cells, due to increased expression of the main glucose transporter GLUT1, which is responsible for the basal transport of monosaccharide\u0026nbsp;[25]. In MCF-7 cells, by enhancing the expression of not only \u003cem\u003eGLUT1\u003c/em\u003e but also \u003cem\u003eGLUT4\u003c/em\u003e, which is activated and the response to specific inducers, e.g., insulin\u0026nbsp;[26]. In MDA-MB-231 cells due to suppression of \u003cem\u003eGLUT1\u0026nbsp;\u003c/em\u003eexpression against the background of increased \u003cem\u003eGLUT4\u003c/em\u003e level. Overall, such changes in glucose transporter mRNA expression confirm the enhancement of glycolysis in\u0026nbsp;BC\u0026nbsp;cells after their co-cultivation with \u003cem\u003eB. animalis\u003c/em\u003e[27]\u003cem\u003e.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe analysis of the redox system state of the studied cells revealed the greatest increase in the ROS concentration in \u003cem\u003eB. animalis\u003c/em\u003e-treated basal subtype MDA-MB-231 cells (more than 4 times compared to intact cells). In the studied cells, G6PD activity correlates with the level of ROS production in a feedback loop. The greatest ROS increase was observed in cells with reduced activity of this enzyme, which may be a consequence of its depletion as a result of excessive use to stabilize the redox homeostasis of MDA-MB-231 and MCF-7 cells, which was disrupted by \u003cem\u003eB. animalis\u003c/em\u003e treatment. Such changes in enzyme activity may also be a consequence of the switching of cell metabolism from PPP to glycolysis\u0026nbsp;[28]. The described changes in G6PD activity correlate with changes in the expression level of the corresponding mRNA in the studied cells.\u0026nbsp;Increased intracellular ROS/RNS activates \u003cem\u003eG6PD\u0026nbsp;\u003c/em\u003emRNA expression, functioning as a defensive, stress-response mechanism [29].\u0026nbsp;Decreased G6PD activity is likely one of the mechanisms associated with decreased proliferation of BC cells, as enzyme deficiency in tumor cells is accompanied by changes in the expression of cell cycle regulatory proteins [30].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe obtained results confirm that \u003cem\u003eB. animalis\u003c/em\u003e-treated BC cells are characterized by a shift in the metabolic profile towards increased glycolysis, inhibition of proliferation and induction of oxidative stress in cells. The most significant changes are experienced by the metabolic activity of luminal subtype BC cells, and the greatest increase in ROS production was found in basal subtype cells\u003cem\u003e.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe study of β-catenin, which is associated with the cadherin system and its appearance in the nucleus indicates that cells acquire the ability to invasion and migration, since the cytoplasmic domain of cadherins binds to β-catenin and p120, which are mediators of the actin cytoskeleton, showed a decrease in the expression of the marker in MDA-MB-231 cells, while in cells with a dominant epithelial phenotype, no changes in the expression of this biomarker were observed. Vimentin levels, a cytoskeletal protein whose expression is characteristic of cells of the mesenchymal phenotype, did not undergo statistically significant changes in BC cells of the high-grade phenotype - MDA-MB-231 under the influence of bacteria, while in T47D cells, induction of the expression of this biomarker was noted under the conditions of exposure to bacteria. Both the number of vimentin-positive cells and the intensity in T47D cells were low, but compared to the negative control - statistically significant.\u003c/p\u003e\n\u003cp\u003eToday it is known that cadherins are transmembrane glycoproteins that support Ca2+-dependent intercellular adhesion bonds and play one of the most important roles in EMT. It is known that the loss or decrease in the expression of E-cadherin plays a significant role in the development of EMT, which is associated, among other things, with a change in a whole group of transcriptional repressors (Zeb-1, Zeb-2, Twist, Snail, Slug) [31, 32]. It was shown that the bacteria caused a statistically significant decrease in the number of cells expressing and the level of E-cadherin expression in\u0026nbsp;high malignant breast cancer cells - MDA-MB-231. While the changes in E-cadherin expression in T47D cells were not significant and statistically insignificant under the conditions of exposure to \u003cem\u003eB. animalis\u003c/em\u003e.\u003c/p\u003e\n\u003cp\u003eTherefore, \u003cem\u003eB. animalis\u003c/em\u003e causes a diverse effect on the expression of markers that characterize the EMT profile of BC cells depending on their their malignancy level of , which also indicates the modulation of cellular plasticity under the conditions of their exposure to microbiota components and requires further study of this phenomenon, since such modulation of plasticity will contribute not only to changing the metastatic characteristics of tumor cells, but also to changing their sensitivity to antitumor agents of different nature and mechanism of action.\u003c/p\u003e\n\u003cp\u003eThus, monitoring and identifying changes in the phenotypic and metabolic characteristics of tumor cells under the influence of modulators of various nature will contribute to the regulation of the behavior of a malignantly transformed cell and, accordingly, its response to antitumor agents.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn summary, it can be stated that Bifidobacterium animalis does not simply modulate individual metabolic or signaling pathways, but triggers a complex reprogramming of BC cells in a direction characteristic of their molecular subtype. For receptor-positive lines, proactive metabolic activation dominates with a possible increase in proliferative potential. In contrast, triple-negative cells showed a response more similar to adaptive, with signs of metabolic imbalance and rearrangement of growth regulatory cascades.\u003c/p\u003e\n\u003cp\u003eSuch differences suggest that the impact of microbiome components on tumor cells may be context-dependent and determined by receptor status, intrinsic metabolic configuration, and the ability of cells to integrate environmental signals. The data support the concept that bacteria can act as modulators of the tumor microenvironment and metabolic plasticity of breast cancer, and open prospects for further study of bacterial metabolites as potential regulators of tumor growth, their metastatic properties, and response to therapy.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was also performed within the framework of the research project “Study of Lactobacilli, Bifidobacteria and Opportunistic Pathogens of the Human Microbiota Influence on the Features of Mechanisms Realization of Metabolic Disturbances in the Tumor Process” (state registration No. 0121U113840) funded by the National Academy of Sciences of Ukraine.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical trial number\u003c/strong\u003e: not applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics, Consent to Participate, and Consent to Publish declarations\u003c/strong\u003e: not applicable.\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eSchiliro C, Firestein BL. Mechanisms of Metabolic Reprogramming in Cancer Cells Supporting Enhanced Growth and Proliferation. Cells. 2021; 10(5):1056. doi: 10.3390/cells10051056. \u003c/li\u003e\n\u003cli\u003eLi M, Bu X, Cai B, Liang P, Li K, Qu X and Shen L. Biological role of metabolic reprogramming of cancer cells during epithelial‑mesenchymal transition (Review). Oncol Rep 41: 727-741, 2019. doi: 10.3892/or.2018.6882. \u003c/li\u003e\n\u003cli\u003eShibue T, Weinberg RA. EMT, CSCs, and drug resistance: the mechanistic link and clinical implications. Nat Rev Clin Oncol. 2017; 14(10):611-629. doi: 10.1038/nrclinonc.2017.44. \u003c/li\u003e\n\u003cli\u003eHuang, Y., Hong, W. \u0026amp; Wei, X. The molecular mechanisms and therapeutic strategies of EMT in tumor progression and metastasis. J Hematol Oncol 15, 129 (2022). https://doi.org/10.1186/s13045-022-01347-8\u003c/li\u003e\n\u003cli\u003eJolly MK, Ware KE, Gilja S, Somarelli JA, Levine H. EMT and MET: necessary or permissive for metastasis? Mol Oncol. 2017; 11(7):755-769. doi: 10.1002/1878-0261.12083. \u003c/li\u003e\n\u003cli\u003eTaki M, Abiko K, Ukita M, Murakami R, Yamanoi K, Yamaguchi K, Hamanishi J, Baba T, Matsumura N, Mandai M. Tumor Immune Microenvironment during Epithelial-Mesenchymal Transition. Clin Cancer Res. 2021; 27(17):4669-4679. doi: 10.1158/1078-0432.CCR-20-4459\u003c/li\u003e\n\u003cli\u003eSciacovelli M, Frezza C. Metabolic reprogramming and epithelial-to-mesenchymal transition in cancer. FEBS J. 2017; 284(19):3132-3144. doi: 10.1111/febs.14090. \u003c/li\u003e\n\u003cli\u003eSciacovelli M, Goncalves E, Johnson TI, Zecchini VR, da Costa AS, Gaude E, Drubbel AV, Theobald SJ, Abbo SR, Tran MG, et al. Fumarate is an epigenetic modifier that elicits epithelial-to-mesenchymal transition. Nature. 2016; 537:544\u0026ndash;547. doi: 10.1038/nature19353. nature19353\u003c/li\u003e\n\u003cli\u003eShaul YD, Freinkman E, Comb WC, Cantor JR, Tam WL, Thiru P, Kim D, Kanarek N, Pacold ME, Chen WW, et al. Dihydropyrimidine accumulation is required for the epithelial-mesenchymal transition. Cell. 2014; 158:1094\u0026ndash;1109. doi: 10.1016/j.cell.2014.07.032. S0092-8674(14)00982-9. \u003c/li\u003e\n\u003cli\u003eKozak, T., Lykhova, O., Chekhun, V. Reprogramming of glucose metabolism in human breast cancer cells after co-cultivation with Bifidobacterium animalis. Experimental Oncology, 2025; 47(1): 3\u0026ndash;15. https://doi.org/10.15407/exp-oncology.2025.01.003\u003c/li\u003e\n\u003cli\u003eCapes-Davis A, Capes-Davis A, Freshney RI. Freshney\u0026rsquo;s culture of animal cells: a manual of basic technique and specialized applications. Eighth edition. Hoboken, NJ: Wiley-Blackwell, 2021.\u003c/li\u003e\n\u003cli\u003eRiisom M, Jamieson SMF, Hartinger CG. Critical evaluation of cell lysis methods for metallodrug studies in cancer cells. Metallomics 2023; 15: mfad048.\u003c/li\u003e\n\u003cli\u003eSolyanik GI, Kolesnik DL, Prokhorova IV, et al. Mitochondrial dysfunction significantly contributes to the sensitivity of tumor cells to anoikis and their metastatic potential. Heliyon 2024; 10: e32626.\u003c/li\u003e\n\u003cli\u003eDetre S, Saclani Jotti G, Dowsett M. A \u0026lsquo;quickscore\u0026rsquo; method for immunohistochemical semiquantitation: validation for oestrogen receptor in breast carcinomas. J Clin Pathol 1995; 48: 876\u0026ndash;878.\u003c/li\u003e\n\u003cli\u003eBhardwaj V, He J. Reactive Oxygen Species, Metabolic Plasticity, and Drug Resistance in Cancer. Int J Mol Sci. 2020; 21(10):3412. doi: 10.3390/ijms21103412\u003c/li\u003e\n\u003cli\u003eZhao J, Jin D, Huang M, Ji J, Xu X, Wang F, Zhou L, Bao B, Jiang F, Xu W, Lu X, Xiao M. Glycolysis in the tumor microenvironment: a driver of cancer progression and a promising therapeutic target. Front Cell Dev Biol. 2024; 12:1416472. doi: 10.3389/fcell.2024.1416472\u003c/li\u003e\n\u003cli\u003eYu L, Chen X, Wang L, Chen S. The sweet trap in tumors: aerobic glycolysis and potential targets for therapy. Oncotarget. 2016; 7(25):38908-38926. doi: 10.18632/oncotarget.7676\u003c/li\u003e\n\u003cli\u003eCiernikova S, Sevcikova A, Stevurkova V, Mego M. Tumor microbiome - an integral part of the tumor microenvironment. Front Oncol. 2022; 12:1063100. doi: 10.3389/fonc.2022.1063100.\u003c/li\u003e\n\u003cli\u003eBottacini F, van Sinderen D, Ventura M. Omics of bifidobacteria: Research and insights into their health-promoting activities. Biochem J. 2017; 474:4137\u0026ndash;4152. doi: 10.1042/BCJ20160756\u003c/li\u003e\n\u003cli\u003eWei H, Chen L, Lian G, Yang J, Li F, Zou Y, Lu F, Yin Y. Antitumor mechanisms of bifidobacteria. Oncol Lett. 2018; 16(1):3-8. doi: 10.3892/ol.2018.8692\u003c/li\u003e\n\u003cli\u003eKozak, T., Lykhova, O. Inhibition of proliferation and increased expression of proapoptotic proteins in human breast cancer cells after their co-cultivation with Bifidobacterium animalis in vitro. Oncology 2024; 25(1): 29\u0026ndash;37 (in Ukrainian). https://doi.org/10.15407/oncology.2024.01.029\u003c/li\u003e\n\u003cli\u003eParisima Karami, Hamid Reza Goli, Saeid Abediankenari, Sneha R. Chandani, Narjes Jafari, Maryam Ghasemi, Mohammad Ahanjan, Anti-tumor effects of Bacteroides fragilis and Bifidobacterium bifidum culture supernatants on mouse breast cancer, Gene Reports, 2023; 33; 101815, https://doi.org/10.1016/j.genrep.2023.101815.\u003c/li\u003e\n\u003cli\u003eXia JQ, Wang YL, Li XL, Wang JN, Li FC, Jia SY, Ba YL, Luo DL, Gao T, Li ZT, Xiao M, Dou H. Lactate dehydrogenase a is a crucial biomarker that affects the prognosis, chemotherapy effect, and immune infiltration of breast cancer. 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Int J Mol Sci. 2020; 21(20):7624. doi: 10.3390/ijms21207624.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-microbiology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"mcro","sideBox":"Learn more about [BMC Microbiology](http://bmcmicrobiol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/mcro","title":"BMC Microbiology","twitterHandle":"#bmcmicrobiology","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"breast cancer, cell culture, Bifidobacterium animalis, epithelial-mesenchymal transition, glucose metabolism, apoptosis","lastPublishedDoi":"10.21203/rs.3.rs-9441737/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9441737/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cem\u003e\u003cstrong\u003eBackground: \u003c/strong\u003e\u003c/em\u003e\u003cem\u003eThe microbiota is an important element of the tumor microenvironment and is able to influence the biological properties of malignant cells, which determine their malignancy and sensitivity to anticancer therapy.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eAim\u003c/strong\u003e\u003c/em\u003e\u003cem\u003e: To investigate the effect of the microbiota member Bifidobacterium animalis (B. animalis) on glucose metabolism, the expression of genes regulating these processes, ROS levels, and the expression of EMT-associated proteins in breast cancer (BC)cells of different molecular subtypes.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eMaterials and methods: \u003c/strong\u003e\u003c/em\u003e\u003cem\u003eBC cell lines: T47D, MCF-7, MDA-MB-231; prokaryotic cells: Bifidobacterium animalis subsp. lactis\u003c/em\u003e BB-12\u003cem\u003e. Metabolic activity of BC cells was determined by biochemical methods. Expression levels of glucose transporters and key enzymes of glycolysis genes were assessed by real-time PCR. Viability of BC cells and ROS production were determined by flow cytometry. Expression of EMT-associated proteins was analyzed by immunocytochemical analysis.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eResults: \u003c/strong\u003e\u003c/em\u003e\u003cem\u003eBCcells treated with B. animalis are characterized by a shift in the metabolic profile towards increased glycolysis, inhibition of proliferation and induction of changes in the redox state of cells.A statistically significant increase in glucose consumption and lactate production rate, lactate dehydrogenase activity was observed in B. animalis-treated BC cells of all three lines.\u003c/em\u003e \u003cem\u003eThe detected changes in mRNA expression of the glucose transporter genes GLUT1 and GLUT4 and the lactate dehydrogenase isoforms LDHA and LDHB confirm that \u003c/em\u003eB. animalis does not simply modulate individual metabolic or signaling pathways, but triggers a complex reprogramming of BC cells in a direction characteristic of their molecular subtype.\u003cem\u003e In B. animalis-treated BCcells G6PD activity correlates with the level of ROS production in a feedback loop. \u003c/em\u003eThe multidirectional influence of prokaryotic members of the microbiome was also revealed when studying the EMT-associated profile of breast cancer cells of different molecular subtypes: the expression of biomarkers differed depending on the initial dominance of epithelial or mesenchymal characteristics.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eConclusions: \u003c/strong\u003e\u003c/em\u003eThe data support the concept that bifidobacteria can act as modulator of the tumor microenvironment and metabolic plasticity of breast cancer cells, and open prospects for further study of bacterial metabolites as potential regulators of tumor growth, their metastatic properties, and response to therapy.\u003c/p\u003e","manuscriptTitle":"Modulation of the Molecular Biological Profile of Breast Cancer Cells by Exposure to Bifidobacterium 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