P values < 0.05. These findings indicate altered sialin mRNA expression in the main tissues of male T2D rats and may have implications for future NO-based treatment of T2D.Nitrate therapy has been suggested to boost nitric oxide (NO) levels in type 2 diabetes (T2D); however, little is known about nitrate transport across the membranes. This study aimed to assess changes in the mRNA expression of sialin, as a nitrate transporter, in the main tissues of rats with T2D. Rats were divided into two groups (n = 6/group): Control and T2D. A high-fat diet combined with a low dose of streptozotocin  was used to induce T2D. At month 6, samples from the main tissues of rats were used to measure the mRNA expression of sialin and levels of NO metabolites. Rats with T2D had lower nitrate levels in the soleus muscle (66%), lung (48%), kidney (43%), aorta (30%), adrenal gland (58%), epididymal adipose tissue (eAT) (61%), and heart (37%) and had lower nitrite levels in the pancreas (47%), kidney (42%), aorta (33%), liver (28%), eAT (34%), and heart (32%). The order of sialin gene expression in control rats was: soleus muscle > kidney > pancreas > lung > liver > adrenal gland > brain > eAT > intestine > stomach > aorta > heart. Compared to controls, rats with T2D had higher sialin mRNA expressions in the stomach (2.1), eAT (2.0), adrenal gland (1.7), liver (8.9), and soleus muscle (3.4), and lower sialin expression in the intestine (0.56), pancreas (0.42), and kidney (0.44), all  Decreased nitric oxide (NO) bioavailability, the amount of NO that becomes available to its targets, is involved in the pathophysiology of T2D2. NO is produced via NO synthase (NOS)-dependent and NOS-independent (nitrate-nitrite-NO) pathways3 that account for about 90% and 10% of the whole-body NO production, respectively4. In the NOS-dependent pathway, NO is synthesized from L-arginine. In the second pathway, NO is produced from the reduction of nitrate and nitrite5, where nitrate has endogenous (oxidation of NOS-derived NO) and exogenous (mainly through diet) sources6. The nitrate-nitrite-NO pathway is complementary to the NOS-dependent pathway8. In support, dietary nitrate/nitrite deprivation leads to decreased skeletal muscle nitrate and nitrite in rats7 and developing metabolic syndrome and endothelial dysfunction in mice9. In T2D, both NO production pathways are disrupted, and decreased endothelial NOS (eNOS) and increased inducible NOS (iNOS) expression and activity11 and impaired nitrate-nitrite-NO pathway12, have been reported.The prevalence of type 2 diabetes (T2D) in adults increased from 151 to 537 million during the last two decades, and it is estimated to reach 783 million by 20455, is now one strategy for NO boosting in NOS-disrupted conditions, including T2D13. Indeed, the beneficial metabolic effects of nitrate/nitrite in rodent models of T2D have been shown15, and the underlying mechanisms include increased insulin secretion from pancreatic β-cells17 as well as improved peripheral glucose utilization21. Stimulatory effect of nitrate/nitrite on insulin secretion in rats with T2D are mediated by increasing pancreatic islets' blood flow16, increasing pancreatic islets' insulin synthesis and exocytosis17, and blunting diabetes-induced oxidative stress in pancreatic islets22. Despite extensive research on the beneficial effects of nitrate and nitrite in T2D, little is known about nitrate transport across the membranes. Nitrate cannot freely permeate through the phospholipid bilayer and needs transporters to move across the plasma membrane23.Intervention by nitrate and nitrite, which have NO-like bioactivity24. Slc17a5 is located on chromosome 6q in humans and 9q in rodents25 and is a highly conserved gene in humans and rodents26. The Slc17 family includes type I phosphate, sialin, vesicular glutamate, and vesicular nucleotide transporters28. Sialin protein has 495 amino acids29 and, in both humans and rodents, is an integral membrane protein that has 12 transmembranes domains30. In 2012, it was reported that sialin could act as a 2NO3−/H+ cotransporter in the salivary glands, which causes nitrate influx to the cell31. Nitrate transport into cells through sialin is essential for the nitrate-nitrite-NO pathway32. Sialin is widely expressed in the eye, brain, liver, pancreas, kidney, muscles, and salivary glands35. This wide expression in almost all tissues in both humans and rodents28 reflects a housekeeping function for this carrier27. Inhibition of sialin or its knockout decreases nitrate uptake in human skeletal muscle cells36 and human submandibular gland cell line (HSG), whereas its overexpression increases nitrate uptake31. In addition, sialin expression increases in hypoxic cancer cells37 and hypercholesterolemic rats' heart and liver tissues38. To our knowledge, changes in sialin gene expression, if any, have not been reported in T2D. Therefore, this study aimed to assess the changes in sialin mRNA expression in the main tissues of type 2 diabetic rats.Slc17a5  gene that encodes sialin protein, was first identified in 199939 and reported following ARRIVE guidelines40. The ethics committee of the Research Institute for Endocrine Sciences affiliated with the Shahid Beheshti University of Medical Sciences confirmed and approved all experimental procedures of the current study .All experiments of the current study were affirmed by the published guideline of the care and use of laboratory animals in Iran41. For the preparation of HFD, 586 g of powdered regular diet, 310 g of sheep butter as a source of fat, 73 g of casein  as a source of protein, 1.8 g, 4.1 g, and 25 g of DL-methionine, vitamin mix, and mineral mix  were thoroughly mixed to produce 1000 g HFD. In the prepared HFD, the total caloric value was ~ 4900 kcal/1000 g, and calories received from fat, carbohydrate, and protein were 58.8%, 27.0%, and 14.2%, respectively. Details on the induction of T2D in rats using combination of HFD and low dose of STZ have been reviewed in our previous report41.Male Wistar rats (n = 12), 2 months old, weighing 190–200 g, were housed in polypropylene cages under standard conditions with free access to regular rat diet  and drinking water. Rats were randomly allocated to 2 groups (n = 6/group): Control and T2D. A high-fat diet (HFD) combined with streptozotocin at a low dose  injection) was used to induce T2D; one week later, anesthetized rats with overnight (12 h) fasting serum glucose concentration ≥ 150 mg/dL were included in the study as diabetic rats42.The protocol for this experimental interventional study is shown in Fig. g) and then the sera were used to measure serum glucose concentrations; the intra-assay coefficient of variation (CV) was 2.6%.Serum glucose concentration was measured at months 0 and 6 by the glucose oxidase method . After overnight fasting (12 h), blood samples were obtained from the tail tips of anesthetized rats (IP injection of ketamine at dose 50 and xylazine at dose 10 mg/kg) and centrifuged  instead of centrifugation by a 30-kDa molecular weight filter as reported by Miranda et al.42; in addition, NaOH (3.72 M44) was used for preventing turbidity in the Griess reaction. After adding zinc sulfate and NaOH to 300 μL of the homogenized tissues, samples were centrifuged , and supernatants were removed o measure of NOx and nitrite levels. In brief, all tissues were homogenized  and 100 mg of the brain and eAT in 200 μL of PBS) and centrifuged for 10 min at 10,000 g. For measuring NOx, nitrate was reduced to nitrite by adding vanadium trichloride , followed by N-(1-naphthyl) ethylenediamine (0.1% in ddH2O) and sulfanilamide (2% in 5% HCl). Samples were kept for 30 min at 37 °C, and optical density (OD) was read at 540 nm. NOx concentrations were measured using a standard calibration curve of 0–100 µM sodium nitrate.The NOx and nitrite concentration in all tissues were measured by the Griess methodNitrite was measured using the same method, except that samples were only exposed to sulfanilamide, NEDD, and 1 M HCl instead of VCL3; nitrite standards (0–20 µM) were used. Tissue nitrate concentrations were calculated by subtracting nitrite values from NOx concentrations. Protein concentration was measured using the Bradford method; nitrite and nitrate concentration in tissues are presented as nmol/mg protein. The intra-assay CVs for NOx in the heart, aorta, stomach, intestine, adrenal gland, liver, lung, pancreas, kidney, brain, eAT, and soleus skeletal muscle were 2.2, 1.7, 2.7, 2.0, 1.4, 2.2, 2.1, 2.5, 2.9, 2.9, 1.8, and 3.5%, respectively. The intra-assay CVs for nitrite in the heart, aorta, stomach, intestine, adrenal gland, liver, lung, pancreas, kidney, brain, eAT, and soleus skeletal muscle were 3.0, 3.6, 2.0, 2.8, 2.8, 4.0, 2.2, 1.5, 2.9, 2.3, 2.5, and 3.2%, respectively.45. For cDNA synthesis, a cDNA synthesis kit , in accordance with manufacturer instructions, and a peqSTAR Universal PCR machine  was used. The reaction contained 1 μg of extracted RNA, 1 μL of ExcelRT Reverse transcriptase (RT) (200 U/μL), 4 μL of RT buffer, 1 μL of random hexamer (100 µM), 1 μL of dNTPS Mix (10 mM), 1 μL of RNAok RNase inhibitor (20 U/μL) and 4 μL of DEPC-treated H2O. The thermal cycling settings included 5 min at 70 °C for RNA denaturation followed by incubation at 25 °C for 20 min and 50 °C for 50 min, respectively.Total RNA from all tissues were extracted using the TRIzol reagent . The purity and quantity of the extracted total RNA was determined using A NanoDrop-1000 spectrophotometer . The 260/280 and 260/230 absorbance ratios were used as indices of RNA purity; a pure RNA sample  is characterized by 260/280 and 260/230 absorbance ratios ranging between 1.8 and 2.22O, yielding a total volume of 25 µL. The thermal cycling settings included a 10 min initial denaturation (95 °C) followed by 40 cycles with 45, 45, and 60 s at 94, 58, and 72 °C, respectively. All tissues were run in duplicate; nuclease-free water was used instead of templates in the negative control reactions. Sequences of primer for sialin and GAPDH (housekeeping) genes are presented in Table 46. GAPDH has relatively stable expression in the liver47, kidney48, pancreas49, heart50, brain51, adipose tissue47, and intestine52 in rodents. In addition, its expression remains relatively stable in the tissues of rodents with T2D53.Finally, amplification of synthesized cDNA was done using SYBR Green PCR Master Mix 2X  in a Rotor-Gene 6000 real-time PCR machine . The reaction contained 2 µL cDNA, 2 μL of primers (forward and reverse), 12.5 μL Master Mix, and 8.5 μL DEPC-treated Hwww.graphpad.com. All values are presented as mean ± SEM, except for mRNA expressions of sialin, which are represented as relative fold changes. A two-way mixed (between-within) analysis of variance followed by the Bonferroni post-hoc test was used to compare body weight and glucose at the start and end of the study among control and T2D rats. The Student's t-test was used to compare the NOx, nitrite, and nitrate levels between groups. To determine the precision of the assays, CV was calculated using the formula: CV = (standard deviation/mean) × 100)]54. Relative expressions of genes were calculated based on cycle thresholds of sialin versus GAPDH as a reference gene using the REST software55. This software uses a randomization test to compare the difference between control and diabetic samples, which avoids any assumptions about data distribution and is therefore preferred over parametric tests55. Quantities of interest in PCR data are derived from ratios and variances can be high, so standard parametric tests, which depend on normal distribution, are inappropriate for their statistical analysis. A randomization test repeatedly and randomly reallocates the observed values to control and treated groups and notes the expression ratio. P values are calculated from the proportion of random allocations of mean observed data to the control and treated groups. Since examining of all possible allocations is impractical, a random sample is drawn; taking 2000 samples or more provides a reliable estimate of P value at 0.05 level55. In addition, REST software provides efficiency-corrected relative gene expression, which is highly recommended55, prevents any miscalculating expression ratio differences56, and allows the comparison of two groups for one reference and one or more target genes55. Two-sided P values < 0.05 and between 0.05 and 0.10 were considered statistically and marginally significant, respectively.Data were analyzed using GraphPad Prism version 8.0.0 for Windows, GraphPad Software, San Diego, California USA, P < 0.001) at month 6. In addition, compared to month 0, serum glucose levels at month 6 were higher by 57% (P < 0.001) in the diabetic rats.As shown in Table P = 0.004), lung , kidney , aorta , adrenal gland , eAT , and heart ; however, nitrate levels were higher in the intestine of diabetic rats  and no changes were observed in the stomach, pancreas, brain, and liver.As presented in Fig. P = 0.009), kidney , aorta , liver , eAT , and the heart . Nitrite values in the soleus muscle, stomach, intestine, lung, adrenal gland, and brain were similar among control and diabetic rats.Compared to controls, rats with T2D had lower values of nitrite levels in the pancreas , kidney , and soleus muscle . mRNA expressions of sialin in the lung of rats were comparable with the liver.If mRNA expressions of sialin in the liver of control rats is considered as reference , in control rats, mRNA expressions of sialin in the heart (0.006-fold), aorta (0.089-fold), stomach (0.11-fold), intestine (0.17-fold), eAT (0.2-fold), brain (0.27-fold), and adrenal gland (0.61-fold) were lower than the liver; all P < 0.001) and kidney  and lower expression in the heart , aorta , stomach , intestine , eAT , and brain . No change was observed in the sialin mRNA expressions in the adrenal gland, lung, and pancreas of diabetic rats, as compared with the expressions in the liver of controls.Compared to mRNA expressions of sialin in the liver of controls, rats with T2D had higher sialin mRNA expression in the soleus muscle , decreased it in some tissues , and did not affect other studied tissues .57, soleus muscle (64%)57, eAT (42%)57, inguinal adipose tissue (30%)15, kidney (42%)58, heart (60%)58, and aorta (40%)59 of rats with T2D as well as lower nitrate (33%) and nitrite (51%) concentrations in the gastrocnemius muscle18 and heart (43%)60 of mice with T2D. In addition, chronic metabolic conditions, including hypertension and T2D, are characterized by reduced NO production61. Decreased NO metabolites in tissues of diabetic rats are due to impaired NOS-dependent NO production, including decreased availability of L-arginine, decreased eNOS expression, increased arginase activity, uncoupling of NOS, and increased levels of asymmetric dimethyl L-arginine 62. In T2D, eNOS is uncoupled and produces superoxide anion instead of NO62. Superoxide anion rapidly reacts with iNOS-derived NO to form peroxynitrite, a potent oxidant, which enhances eNOS uncoupling63 by increasing intracellular ADMA levels  and oxidation of tetrahydrobiopterin (an eNOS cofactor)65. In addition, oxidation of eNOS by peroxynitrite66, may be an essential mechanism in the development of eNOS uncoupling and decreased NO metabolites in diabetic conditions. The impaired nitrate-nitrite-NO pathway is also involved in NO deficiency in T2D and is due to decreased reduction of nitrate to nitrite and then to NO because of oral microbiota dysbiosis, which decreases oral nitrate-reducing bacteria, abnormal metabolism of ascorbic acid, which decreases gastric conversation of nitrite to NO, and decreased nitrate-nitrite reductase enzymes69.Our results indicate that except for the brain, stomach, and intestine, in other studied tissues, lower values of nitrate  or nitrite  are observed in diabetic rats. These results represent a generalized decreased NO bioavailability in T2D and are in line with other reports indicating lower NOx concentrations in the liver (43%)31, indicating species difference in the tissue pattern of sialin expression. These findings are supported by data showing species differences in NO metabolism; it has been reported that NO production in the rat (0.55 ± 0.05 μmol/kg/h) is similar to humans (0.38 ± 0.06 μmol/kg/h) but it is about 20 times higher in mice (7.68 ± 1.47 μmol/kg/h)61. In addition, the accumulation of nitrate in the saliva (with a concentration 10–20 fold higher than blood) in humans is more effective than in rodents; however, nitrate reduction in basal conditions in rodents is more effective than humans61.In our study, the order of sialin expression in tissues of control rats  was different from those reported for humans (brain > kidney > liver > pancreas) and pigs (liver > brain > kidney > muscle > pancreas)70, and this compensatory pathway partially sustains NO bioavailability in myoglobin-deficient mice70. Moreover, it has been reported that a decrease in dietary nitrate for 21 days that causes decreased nitrate levels in the soleus muscle is associated with increased sialin expression by 50% in rats71.Compared to the controls, in rats with T2D, sialin mRNA expression was higher in the adrenal gland, eAT, stomach, soleus muscle, and liver. Conversely, it was lower in the intestine, pancreas, and kidney. In most studied tissues, increased sialin mRNA expression in diabetic rats was accompanied by decreased nitrate and nitrite concentrations, suggesting that increased sialin mRNA expression acts as a compensatory mechanism to counteract reduced NO bioavailability. In support of this notion, it has been reported that sialin expression in the skeletal muscle of control mice increased by 89% upon deletion of myoglobin, which reduces nitrite to NO72. Our finding that sialin mRNA expression was highest in the skeletal muscle is in line with the hypothesis proposed by Piknova et al. that skeletal muscle tissue is the main nitrate reservoir organ and the liver and other organs are the final site of reduction of nitrate to nitrite and then NO73. According to this hypothesis, due to its large size and low nitrate reductase activity, skeletal muscle is an optimal place to store nitrate and may have a protective role against possible future periods of dietary nitrate deprivation, at least in rodents73.In the current study, sialin mRNA expression was lowest in the heart and highest in the soleus muscle. It has been reported that NO production in the heart of normal Wistar rats mainly relies on the NOS-dependent rather than the nitrate-nitrite-NO pathway; indeed, NOS-dependent and -independent pathways contribute about 80% and 20% to the total heart NO formation, respectively. However, in the ischemic heart, NO formation from the NOS-independent pathway increases and can exceed NOS-dependent NO generation74, male pigs, and male humans31, suggests that sialin may contribute to renal reabsorption of nitrate75. Therefore, it is expected that decreased sialin mRNA expression in the kidney would be accompanied by reduced nitrate and nitrite levels. However, our data cannot explain the causality between nitrate/nitrite deficiency and sialin expression, and this issue needs further investigation.In our study, decreased sialin mRNA expression was accompanied by reduced nitrate/nitrite levels in some tissues . Therefore, whereas nitrate deficiency in T2D was associated with increased sialin mRNA expression in some tissues  due to a compensatory response, it was associated with decreased sialin mRNA expression in some other tissues. Although not completely understood, high apical expression of sialin in the kidney distal tubule cells of female mice76. In this model, consumption of HFD induces insulin resistance, and subsequently, administration of STZ at a low dose causes partial destruction of pancreatic β-cells41 by apoptosis77. Increased apoptosis is responsible for impaired insulin secretion in pancreatic β-cell in both humans and rats79. We used low dose of STZ along with HFD, as it has been reported that the animals fed only with HFD for 276, 480, 1681, and 3682 weeks progressed insulin resistance but not hyperglycemia.As a strength, we used an HFD/low-dose STZ model of T2D, which mimics the pathophysiology of T2D in humans by inducing long-lasting and stable hyperglycemia, insulin resistance, relative hyperinsulinemia, hypertriglyceridemia and also it is sensitive to glucose-lowering effects of metformin and troglitazone83 and diabetic (~ 60%)84 rats. However, the hyperglycemic effect of ketamine/xylazine is acute (observed only 6–22 min after IP injection83) and mainly observed in fed, not fasted rats86. We measured our serum glucose values after overnight fasting and therefore it is unlikely that our data was affected by use of ketamine/xylazine.As a limitation, we used ketamine/xylazine to anesthetize rats that can increase blood glucose in normal (~ 40%)31, these data may have implications for future NO-based treatment of T2D, which has been suggested to be a cost-effective approach87. Further studies are needed to elucidate the role of sialin in the pathophysiology of T2D.In conclusion, our results indicated altered sialin mRNA expression, as a nitrate transporter, in the main tissues of male T2D rats. It seems that increased sialin mRNA expression in some tissues  may act as a compensatory mechanism to counteract reduced NO bioavailability; however, this hypothesis does not explain decreased mRNA expression of sialin in the pancreas and kidney. Since sialin can play an important role in the physiological regulation of systemic nitrate–nitrite–NO balanceSupplementary Information.


Cancer stem cells (CSCs) are thought to be involved in tumor initiation and recurrence, which makes them pivotal therapeutic targets. However, the molecular circuits behind CSC characteristics are not fully understood and the low number of CSCs is an obstacle for conducting tests that explore their properties. Thus, increasing the number of these cells via small molecule-mediated cellular reprogramming seems a valid alternative tool. Using the SORE6-GFP reporter system, based on SOX2/OCT4 activity and incorporated in gastric non-CSCs, we performed a high-throughput drug screen to identify small molecules capable of converting non-CSCs into CSCs. Our results show that ciclopirox olamine (CPX) is able to reprogram gastric cancer cells to a stem-like phenotype via SOX2 expression, reprogram cell metabolism, and induce senescence. Furthermore, these results suggest that the CSC phenotype is a resistance mechanism to CPX treatment, which is being considered as a repurposing drug for cancer treatment.2), a hypoxia-mimetic agent.Cancer stem cells (CSCs) are relevant therapeutic targets for cancer treatment. Still, the molecular circuits behind CSC characteristics are not fully understood. The low number of CSCs can sometimes be an obstacle to carrying out assays that explore their properties. Thus, increasing CSC numbers via small molecule-mediated cellular reprogramming appears to be a valid alternative tool. Using the SORE6-GFP reporter system embedded in gastric non-CSCs (SORE6−), we performed a high-throughput image-based drug screen with 1200 small molecules to identify compounds capable of converting SORE6− to SORE6+ (CSCs). Here, we report that the antifungal agent ciclopirox olamine (CPX), a potential candidate for drug repurposing in cancer treatment, is able to reprogram gastric non-CSCs into cancer stem-like cells via activation of SOX2 expression and increased expression of C-MYC, HIF-1α, KLF4, and HMGA1. This reprogramming depends on the CPX concentration and treatment duration. CPX can also induce cellular senescence and the metabolic shift from oxidative phosphorylation (OXPHOS) to glycolysis. We also disclose that the mechanism underlying the cellular reprogramming is similar to that of cobalt chloride (CoCl Gastric cancer is the fifth most commonly diagnosed cancer and the fourth deadliest cancer in the world . The seaRecently, we have transduced two gastric cancer cell lines with the SORE6−GFP reporter system developed by Tang et al., which relies on the activity of the transcription factors (TFs) SOX2 and OCT4 to drive the expression of the GFP reporter, i.e., after incorporation of the reporter system into cells, those that express sufficient levels of SOX2 and/or OCT4 will activate GFP expression, while those that do not express sufficient levels of these TFs remain GFP-negative ,11. Two Cellular reprogramming is an interesting approach for converting cancer cells into CSCs to produce a greater CSC population for experimental manipulation and to explore the molecular mechanisms that induce the CSC phenotype ,13. Repr2, a hypoxia-mimetic agent that stabilizes the expression of HIF-1α.Via high-throughput screening of small molecules, we identified a compound capable of reprogramming gastric cancer cells into CSCs. Here, we report that the small molecule CPX, an iron chelator, has a potent cytotoxic effect on gastric cancer cells, but it can also reprogram gastric non-CSCs to a cancer stem-like cell phenotype, depending on the dose and treatment duration. CPX can promote the metabolic shift from OXPHOS to glycolysis, induce cellular senescence, and increase the expression of several TFs associated with stemness features such as SOX2, C-MYC, HIF-1α, KLF4, and HMGA1. Furthermore, we showed that the mechanism underlying this cellular reprogramming is similar to that of CoClv/v) CO2. When the cell cultures reached a confluence of around 80% they were trypsinized with 0.05% Trypsin-EDTA (1X)  and sub-cultured or used in cell-based assays.Four human gastric carcinoma cell lines  established under the scope of previous work  were use4 cells/mL in RPMI medium 1640 with 25 mM HEPES and GlutaMAX-1 supplemented with 10% FBS. High-throughput screening of 1200 compounds from the Prestwick Chemical Library was performed as described in [AGS SORE6− cells  were seeribed in . Brieflyribed in . The ima4 cells/mL and allowed to attach overnight. Cells were then incubated for 48 h with various concentrations (0.125–16 μM) of ciclopirox olamine   or 0.4% DMSO. To assess cell viability and GFP expression, cells were fixed, stained, and analyzed using the INCell Analyzer 2000 and INCell Investigator software, as described in the Materials and Methods High-throughput screening of the Prestwick chemical library. To further explore the effect of CPX on cell viability and activation of the SORE6−GFP reporter system, AGS SORE6− cells were seeded in 12-well plates at a density of 1 × 105 cells/mL and allowed to settle for 24 h. Then, cells were exposed to 4 or 8 μΜ CPX for 2, 6, 12, 24, or 48 h. For cytotoxicity assessment, culture media was discarded, adherent cells were washed with phosphate-buffered saline (PBS) 1x , and 50 μL of PrestoBlue Cell Viability Reagent 1x (ThermoFisher Scientific) prepared in RPMI complete medium was added. Cells were incubated for 1 h and 10 min at 37 °C in a 5% CO2 humidified atmosphere, protected from light. The absorbance was measured at 560 nm (using 600 nm as a reference wavelength) using a BioTek Synergy 2 multi-mode microplate reader . GFP expression was evaluated using a FACSCanto II flow cytometer . The data were analyzed using FlowJo software (version 7.6.1). Cells treated with 8 μM CPX for 24 or 48 h were left in culture for a total of 5 weeks. Every week, cells were collected by trypsinization and centrifuged at 350 rcf for 5 min at room temperature (RT), and cell pellets were used for Western blot and flow cytometry analysis of GFP expression. AGS SORE6− cells and Kato III SORE6− cells were also seeded in 6-well plates at a density of 1.5 × 105 cells/mL and 2 × 105 cells/mL, respectively, and allowed to attach overnight. Cells were then incubated with 2, 4, 8, or 16 μM CPX or 0.4% DMSO for 48 h. After, cells were collected, and cell pellets were used for Western blot and/or real-time PCR analysis. Cells treated with DMSO were used as a negative control. CPX effect was also assessed in CPX-recovered cells. For this, four weeks after exposure to DMSO or 4 or 8 μM CPX, AGS SORE6− and Kato III SORE6− recovered cells were plated in 12-well plates at a density of 1 × 105 cells/mL in RPMI with 10% FBS and allowed to attach overnight. Cells were then exposed for 48 h to 8 μM CPX. For the cytotoxicity assessment, the PrestoBlue assay was performed as described above. The cells were collected and used for flow cytometry and Western blot analyses. Cells treated with DMSO were used as a negative control.AGS SORE6− cells were seeded in 96-well plates  at a density of 5 × 10The preparation of whole cell extracts and protein quantification were conducted as detailed in . Briefly−ΔΔCT method [Total RNA extraction using TRI Reagent  was performed according to the manufacturer’s protocol instructions. RNA concentration and quality were evaluated using a NanoDrop ND-1000 spectrometer (V3.5.2 Software). Total RNA (1 μg) was converted to cDNA in a thermocycler  in a final reaction volume of 20 µL, containing 1 µL of random primers (100 ng/µL) , 1 µL of dNTPs (10 mM) (Invitrogen), 2 µL of 10× Reaction Buffer , 0.2 µL of RNAseOUT (40 U/µL) (Invitrogen), and 0.5 µL of NZY Reverse Transcriptase (200 U/µL) (NZYTech) in DEPC-treated water (Invitrogen). For the PCR, each reaction was prepared as described in . Primer T method .5 cells/mL and 1.5 × 105 cells/mL, respectively, and allowed to settle for 24 h. Afterward, cells were incubated with 100, 200, or 300 μM CoCl2 for 48 h. Cells were collected and cell pellets were used for Western blot and/or real-time PCR and flow cytometry analysis of GFP expression. Cytotoxicity assessment was performed using PrestoBlue Cell Viability Reagent 1x as described above. Untreated cells (only incubated with complete medium) were used as a negative control.AGS SORE6− and Kato III SORE6− cells were seeded in 12-well plates at a density of 1 × 102 or were plated in 6-well plates at a density of 300 cells per well and 1500 cells per well, respectively. Cells were left undisturbed for 10 days at 37 °C and 5% (v/v) CO2, except for the fifth day, when the medium was changed. After 10 days, colony formation was visualized by staining the cells with a 1% crystal violet solution diluted in PFA for 30 min. The number of colonies per condition was assessed with the ImageJ software.AGS SORE6− cells and Kato III SORE6− cells were treated with CPX or CoCl4 cells/mL and incubated with RPMI medium for 24 h. Then, cells were treated with CPX (4 μM and 8 μM) or CoCl2  for 48 h. After, cells were washed and incubated with XF DMEM Medium  supplemented with 10 mM of XF glucose, 2 mM of XF L-glutamine and 1 mM of XF pyruvate, at 37 °C for 1 h in the absence of CO2. Next, the real-time ATP rate assay was performed using the Seahorse XF Real-Time ATP Rate Assay Kit (Agilent Technologies) according to Agilent’s recommendations, on the Seahorse XFe24 analyzer (Agilent Technologies). There, the baseline oxygen consumption rate (OCR) was measured, followed by sequential OCR measurements via the sequential injection of Oligomycin and Rotenone/Antimycin A. The ratio between the ATP production rate in the glycolytic pathway (glycoATP) and the ATP production rate from mitochondrial oxidative phosphorylation (mitoATP)—ATP rate index—was used as a parameter to identify changes in metabolic phenotype OCR values. Assays were normalized to the total number of cells in each well and analyzed with Agilent Seahorse Analytics.SORE6− cells were seeded in Agilent Seahorse XF24 24-well cell culture microplates at a density of 6 × 105 cells/mL in RPMI with 10% FBS and allowed to attach overnight. Cells were treated with CPX (4 and 8 μM) or CoCl2  for 48 h. After, cells were washed with PBS 1× and fixed with 4% PFA, for 5 min at RT. Subsequently, cells were incubated for 16 h at 37 °C in the absence of CO2 in fresh SA-β-gal staining solution prepared as in Dimri et al. [2, respectively.Cells were plated in 12-well plates at a density of 1 × 10i et al. . SenesceCells were cultured as described in . For celt-test or one-way ANOVA followed by Tukey’s post hoc test using the GraphPad Prism 5.0 software . Differences were considered significant at p ≤ 0.05.The results are expressed as the mean ± standard deviation (SD) from at least three independent experiments. Statistical significance was determined by unpaired two-tailed To identify new drugs that could be used to reprogram gastric cancer cells into CSCs, we screened 1200 compounds from the Prestwick chemical library in previously obtained AGS SORE6− cells (non-CSCs)  and evalTo further explore the potential of CPX for cellular reprogramming, we performed a time-course analysis  of AGS SORE6− cells treated with 4 and 8 µM CPX. Cell evaluation at 2 and 6 h treatment, showed no effect of CPX in the activation of the reporter system nor on cell viability A,B. At 1CSCs show metabolic plasticity, and therefore, one of the relevant characteristics of CSCs is their metabolic phenotype . To asseAs mentioned above, senescence drives the reprogramming of cancer cells and promotes CSC generation . Recent 2, a hypoxia-mimetic agent capable of increasing the expression of stem cell markers . To achieve this, we treated AGS SORE6− and Kato III SORE6− cells with different CoCl2 concentrations for 48 h. Activation of the SORE6-GFP system was observed in both cell lines after treatment with 200 and 300 µM CoCl2  . Our results confirmed that treating AGS SORE6− cells for 48 h with 8 µM CPX significantly increased the expression of HIF-1α A. Since − cells) B,C. In a− cells) D,E. Althreatment F. To rulobserved . Additioycolysis –E. CoCl2oduction . The ratfor 48 h . Overallferation . Becaused HIF-1α A,D,E, wed HIF-1α . In Katod HIF-1α . Notablyd HIF-1α G. In AGSd HIF-1α G. Simila6− cells G. In Katand OCT4 G.CSCs constitute a very small population of cells present in the tumor. Evidence from experimental models and clinical studies indicates that CSCs are responsible for therapy resistance and disease recurrence ,33,34. THere, we used our previously established and characterized CSC model , which i3+ and Fe2+) chelator [2, a well-known hypoxia-mimetic agent that stabilizes HIF-1α expression by blocking its degradation [2 treatment promotes the expression of stem cell markers such as SOX2, OCT4, C-MYC, and NANOG in a dose-dependent manner [2 treatment increased the expression of SOX2, C-MYC, KLF4, OCT4, NANOG, and HMGA1, showing similarities with the effect of CPX in promoting CSCs by upregulating the same set of TFs. Lopez-Sánchez et al. reported that treatment of colon cancer cells with CoCl2 gave rise to polyploid giant cells (larger cells and greater nuclear size) with cancer stem-like features [2 treatments in the two gastric cancer cell lines we have studied. Similarly to CPX, CoCl2 treatment also demonstrated pro-senescent activity and promoted a metabolic shift towards glycolysis, reducing OXPHOS. Metabolically, CSCs can change the way they obtain ATP, depending on the type of tumor and the conditions of the tumor microenvironment. For example, in hypoxic environments, CSCs appear to prefer producing ATP via glycolysis rather than OXPHOS, even in the presence of oxygen (Warburg effect) [CPX has been reported to be associated with OXPHOS inhibition, and it also showed pro-senescent activity, linked to its activity as an iron  ,58,59. W effect) ,61.Together, our results, although supporting the powerful cytotoxic effect of CPX on tumor cells, also recommend care if its therapeutic use is intended, since it may kill most tumor cells but may also convert surviving cells into CSCs. At least at certain concentrations and exposure times, the potential for cellular reprogramming is present via induction of cellular senescence (which can be reversed), metabolic plasticity, and increased expression of stemness markers . Therefore, CPX may be a useful tool for obtaining gastric cancer stem-like cells from non-CSCs, particularly when cells previously treated with CPX are re-exposed to the compound. On the other hand, in an anti-tumor context, to potentiate its cytotoxic effect and avoid cellular reprogramming of gastric non-CSCs towards a stem-like state, adjustments in CPX concentration and exposure period should be evaluated.


The epithelial-mesenchymal transition (EMT) promotes cell signaling and morphology alterations, contributing to cancer progression. Exosomes, extracellular vesicles containing proteins involved in cell-cell communication, have emerged as a potential source of biomarkers for several diseases.Our aim was to assess the proteome content of exosomes secreted after EMT-induction to identify potential biomarkers for ovarian cancer classification. EMT was induced in the ovarian cancer cell line CAOV3 by treating it with EGF (10 ng/mL) for 96 h following 24 h of serum deprivation. Subsequently, exosomes were isolated from the supernatant using selective centrifugation after decellularization, and their characteristics were determined. The proteins present in the exosomes were extracted, identified, and quantified using Label-Free-Quantification (LFQ) via Liquid Chromatography-Tandem Mass Spectrometry (LC-MS/MS). To identify potential biomarkers, the obtained proteomic data was integrated with the TGGA database for mRNA expression using principal component analysis and a conditional inference tree.The exosomes derived from CAOV3 cells exhibited similar diameter and morphology, measuring approximately 150 nm, regardless of whether they were subjected to EMT stimulation or not. The proteomic analysis of proteins from CAOV3-derived exosomes revealed significant differential regulation of 157 proteins, with 100 showing upregulation and 57 downregulation upon EMT induction. Further comparison of the upregulated proteins with the TCGA transcriptomic data identified PLAU, LAMB1, COL6A1, and TGFB1 as potential biomarkers of the mesenchymal HGSOC subtype.The induction of EMT, the isolation of exosomes, and the subsequent proteomic analysis highlight potential biomarkers for an aggressive ovarian cancer subtype. Further investigation into the role of these proteins is warranted to enhance our understanding of ovarian cancer outcomes.The online version contains supplementary material available at 10.1186/s13048-023-01304-0. Ovarian cancer has the highest mortality rate among gynecological neoplasms. Of 314,000 women diagnosed worldwide in 2020, approximately 65% would die from the disease [Epithelial-mesenchymal transition (EMT) is a biological process associated with the development and progression of malignant tumors, involving cell motility and invasion, resistance to apoptotic stimuli, and acquisition of stemness. However, the precise connection between EMT and in vivo metastases remains unclear .Exosomes, which are nanometer-sized vesicles, serve as mediators of intercellular communication by transferring proteins, genes, chemokine receptors, soluble factors, miRNAs, and other bioactive material. Tumor-derived extracellular vesicles are believed to contribute to the development and progression of cancer through various mechanisms, including the activation of hematopoietic and stromal cells, stimulation of angiogenesis , promotiThe discovery of proteins that regulate neoplastic growth and metastasis holds the potential to yield new biomarkers for early detection and prognosis of ovarian cancer, as well as targets for treatment. In this study, our objective was to identify potential biomarkers present in exosomes derived from ovarian cancer cells during the EMT process. We achieved this by employing mass spectrometry to identify proteins and comparing the results with publicly available gene expression data.2. Before use, the cell lines were authenticated by short tandem repeat (STR) profiling and confirmed to be mycoplasma negative [CAOV3 (ATCC® HTB-75™) and SKOV3 (ATCC® HTB-77™) cells lines were cultured in Dulbecco’s modified Eagle medium (DMEM)  supplemented with 10% fetal bovine serum (FBS) . The OVCAR3 (ATCC® HTB-161™) cells were cultured in Roswell Park Memorial Institute Medium (RPMI-1640) (Gibco) supplemented with 20% Fetal Bovine Serum (FBS). Both media were further supplemented with 100 U/mL penicillin and 100 µg/mL streptomycin (Gibco). The cells were maintained at 37◦C in a humidified incubator in an atmosphere of 5% COThe cell lines were initially seeded in the supplemented medium. After 24 h, the cell lines were washed twice with PBS, and the media was replaced with an FBS-free medium. Following additional 24-hour incubation, the cells were treated with an FBS-free medium containing 10 ng/mL Epidermal Growth Factor (EGF) . The EGF-containing medium was replenished every 24 h for a total duration of 96 h [The cells were washed with PBS twice and subsequently disrupted in lysis buffer  using three sonication cycles. Each sonication cycle lasted for 5 min with cooled water in an ultrasonic bath . Following sonication, the cell lysate was centrifuged at 20,000×g for 30 min at 4◦C. The supernatant containing the proteins of interest was collected, and the protein concentration was determined using the Bradford method . Finally, the samples were stored at -80◦C.The proteins were separated by SDS–PAGE and then electrotransferred onto PVDF membranes . Next, the membranes were incubated with blocking buffer (25 mM Tris-HCl (pH 7.5), 0.5 M NaCl, and 0.1% Tween-20) containing 5% non-fat dry milk. Primary antibodies were added to the membranes, followed by incubation with a secondary antibody, specifically horseradish peroxidase-conjugated goat anti-rabbit IgG , as per the manufacturer’s instructions. The primary antibodies used are listed in Supplementary Table The PathScan EGFR signaling array kit  was utilized, which contains fixed antibodies specific to phosphorylated proteins in a chemiluminescent sandwich immunoassay format. Experiments were conducted following the manufacturer’s instructions. Densitometric analyses of the obtained data were performed using the protein array analyzer plugin for ImageJ software.2 atmosphere. ROS using a FACSCalibur cytometer (Becton-Dickinson), and the fluorescence was detected in the FL1/FL2 channel. The acquired data were analyzed using FlowJo software .The production of reactive oxygen species (ROS) was assessed using the intracellular fluorogenic reagent CM-H2DCFDA  according to the manufacturer’s instructions. To serve as controls, cell lines were incubated with PMA (50 nM) for 1 h to induce ROS accumulation through PKC activation. For the experimental groups, CAOV3, SKOV3, and OVCAR3 (both CT and EGF-treated) cell lines were incubated with 5 µM CM-H2DCFDA for 1 h before analysis. The analysis was performed at 37 °C in a 5% CO2 atmosphere using a Varioskan LUX Multimode Microplate Reader. The reader settings included excitation around 550 nm and emission around 580 nm.The assessment of mitochondrial membrane potential was conducted using intracellular tetramethylrhodamine ethyl ester perchlorate (TMRE) , following the manufacturer’s instructions. To establish control, cell lines were incubated with carbonylcyanide 3-chlorophenylhydrazone (CCCP) (50 µM) at 37 °C for 15 min to disrupt the mitochondrial membrane potential. For the experimental groups, CAOV3, SKOV3, and OVCAR3 (both CT and EGF-treated) cell lines were incubated with 200 nM of TMRE for 20 min before analysis. The analysis was performed at 37 °C in a 5% COoC for 30 min. The resulting supernatant was then filtered using a 0.22 μm syringe filter for decellularization. Subsequently, the filtered solution was concentrated to a minimum volume of approximately 8 mL using an Amicon ultrafiltration system with a 100-kDa cutoff . The exosomes were isolated and separated from the concentrated solution using the exoEasy Maxi kit  as per the manufacturer’s instructions. Once isolated and separated, the, collected exosomes were stored in a freezer − 80oC.Following the EMT induction, the culture medium was collected and subjected to centrifugation at 300×g for 10 min, followed by an additional centrifugation step at 3000×g at 4The size, distribution, and quantification of the exosomes obtained from independent experiments were assessed using nanoparticle tracking analysis (NTA) performed on a NanoSight NS300 system . The NTA data were analyzed using NanoSight software (version 3.2.16) .oC for 2 h. After centrifugation at 16,500×g for 30 min, the exosomes were resuspended in PBS and applied onto Formvar/carbon-coated electron microscopy grids. The exosomes were then visualized by negative contrast using a transmission electron microscope JEM-100 CX II (Jeol) equipped with a digital camera Hamamatsu ORCA-HR at magnifications of 50000 ×, 100000 ×, and 200000 × [Freshly isolated exosomes were fixed in phosphate buffer containing 3% glutaraldehyde (v/v) and 4% paraformaldehyde (v/v) at 4200000 × .The proteins were extracted from exosomes by disrupting them using a lysis buffer , 0.5% Octyl β-D-glucopyranoside (O.G) , and protease and phosphatase inhibitors . The disruption process involved three sonication cycles, with each cycle lasting 5 min using cooled water in an ultrasonic bath . After sonication, the samples were centrifuged at 20,000×g for 30 min at 4◦C. The supernatant was collected and the protein concentration was determined by the BCA protein assay kit .oC and alkylated (5:1 mg/mg). The proteins were separated by SDS-PAGE using 4–20% Mini-PROTEAN TGX Precast Protein Gels, Cat # 4561093, Bio-Rad). After SDS-PAGE, each gel lane was divided into 4 equal-sized pieces, and in situ digestion was performed individually for each piece.The exosome proteins (5 µg) were first reduced with DTT (1:1 mg/mg) for 5 min at 954HCO3 (50 mM) containing 50% acetonitrile (ACN), followed by a wash with pure ACN. The slices were dried in SpeedVac (Savant) and then rehydrated with 20 µL of NH4HCO3 (100 mM) containing 0.6 µg of trypsin (Promega) for approximately 30 min. The gel slices were then covered with sufficient NH4HCO3 (100 mM) and maintained at 37oC for 16–18 h for digestion.For each gel slice, SDS and dye were removed using NH™ columns  following the manufacturer’s instructions.After digestion, the peptides were extracted from the gel using an ACN gradient  containing 0.1% formic acid. The extracted peptides were successively transferred to a clean microtube and dried using a SpeedVac (Thermo Scientific). The dried samples were resolubilized in ACN 5% containing 0.1% formic acid and desalted using C18 Zip TipsFor capillary liquid chromatography, an equivalent of 1 µg digested proteins was injected onto a column with dimensions of 25 cm length x 100 μm internal diameter of column). The peptides were separated using a linear gradient of ACN (5 to 35%) containing 0.1% formic acid over a period of 90 min at a flow rate of 250 nL/min. The chromatographic system was coupled to a high-resolution mass spectrometer, Q-Exactive HF (Thermo Scientific). The mass spectrometer was operated with a capillary voltage of 3.2 kV, a capillary temperature of 200 °C, a resolution of 100,000, and an FT-target value of 1,000,000.The spectra were acquired in a dependent mode, selecting the 15 most abundant ions with a + 2 or + 3 charge state in the range of 400 to 1600 m/z for HCD (Higher-energy C-trap dissociation) fragmentation and MS/MS analysis. To avoid peptide sequencing redundancy, a 45-second exclusion window was applied.The six separate files generated from the LC-MS/MS analysis were processed using the Maxquant quantitative proteomics software tool . This soThe search criteria used during the analysis were as follows: trypsin enzyme with a tolerance of two lost cleavages, mass error tolerance for precursor peptide was 6 ppm in the main search, mass tolerance of 20 ppm for fragment ions (MS/MS); and false positive rate (FDR) of 1% for both proteins and peptides.The identified proteins were subjected to relative LFQ, where the normalized intensity profiles (LFQ intensity) were calculated. For paired comparisons, at least 1 peptide identified by MS/MS was required (LFQ minimum ratio count = 1). The normalized intensity values (LFQ intensity) obtained from the analysis were used for statistical analyses using Perseus software version 1.6.7.0 .http://string-db.org/). This allowed us to explore the functional relationships and interactions among the identified proteins.The list of quantified proteins that showed regulation (< 0.5 and > 1.9) from our large-scale proteomics study was subjected to further analysis using public databases and available free open-source software. For the identification, clustering, and visualization of protein-protein interaction networks, we utilized the database STRING  analysis using FunRich . FunRichhttp://www.cbioportal.org/).To prioritize target candidate proteins, we used gene expression data of 489 HGSOC available in The Cancer Genome Atlas (TCGA) database. The samples were clustered into the molecular subtypes immunoreactive (110), mesenchymal (108), proliferative (136), and differentiated (133) , The genhttps://www.r-project.org/) software. We utilized the singular value decomposition for principal component analysis (PCA) to identify major sources of variation in the gene expression data. This allowed us to gain insights into the overall patterns and relationships among the samples based on their gene expression profiles.To integrate and analyze the data, we employed R 4.1.1  and p44/42 MAPK (Thr202 and Tyr204) in both OVCAR3 and SKOV3 cell lines.  in the exosomes secreted by CAOV3 cells. Among them, 157 proteins exhibited differential detection between exosomes from EMT-induced and control cells, with 57 proteins down accumulated and 100 proteins up accumulated , mesenchymal (108), proliferative (136), and differentiated (133) . We emplFigure Figure Our study revealed that EMT induction enhances the concentration of exosomes secreted by ovarian cancer cells, and these exosomes carry potential tumor markers associated with the mesenchymal HGSOC subtype. Through evaluating changes in the proteome of exosomes derived from EGF-stimulated CAOV3 cells and integrating the data with the mRNA expression profile of the HGSOC from the TCGA-OV cohort, we identified PLAU, LAMB1, COL6A1, and TGFB1 as potential markers of mesenchymal HGSOC subtype.The CAOV3 EMT induction model was previously developed by our research group to emulate key aspects of cancer progression and metastasis , 14. TheIn a study by Grassi et al.  the cellEMT potentially plays a significant role in the outcomes of HGSOC, which is a highly lethal gynecological malignancy . EMT endExosomes serve as carriers for a diverse range of molecules, including proteins, nucleic acids, lipids, and metabolites. In our study, among the differentially accumulated proteins in exosomes from EMT-induced cells and controls, a significant number belonged to lysosomes, nucleosomes, and proteasomes. The analysis of vesicles derived from tumor cells, as well as non-classical secretion processes, revealed intracellular proteins within extracellular vesicles , 22, 23.The integrated analysis of EMT-induced exosome proteomic data and TCGA-OV cohort gene expression z-scores  identifiThe gene LAMB1 encodes laminin subunit beta 1. Laminins play a role in cell differentiation, migration, adhesion, and tumor cell invasiveness ,. LAMB1 In osteosarcoma and lung metastasis, COL6A1 is associated with a worse prognosis. Additionally, COL6A1 can be transported by exosomes and influence the differentiation of normal fibroblasts into cancer-associated fibroblasts. This process, driven by TGF/COL6A1 signaling, promotes cell metastasis, invasion, and migration . In ovarThe role of TGFBI in cancer is ambiguous. Hypermethylation of the TGFB1 promoter has been associated with the suppression of TGFB1 expression . TGFB1 iWhile our study has provided valuable insights into the proteomic analysis of exosomes secreted during EMT in CAOV3 cells and the identification of potential biomarkers for mesenchymal HGSOC, we recognize the limitation of utilizing a single cell line in the first step of our investigation. Future studies should consider incorporating multiple cell lines in all steps of the study to enhance the generalizability of our findings and to validate the clinical relevance of these potential biomarkers.Proteomic analysis of exosome proteins from multiple cell lines offers great potential for advancing our understanding of ovarian cancer biomarkers. This approach provides valuable tools for characterizing biomarkers associated with the disease. In our study, we successfully identified and validated candidate biomarkers in EMT-induced TP53 mutant ovarian cancer cell lines, shedding light on their relevance in ovarian cancer progression. The integration of experimental induction of EMT, exosome purification, large-scale proteomic analysis, and integration with gene expression data from the TCGA database allowed us to identify potential markers of the mesenchymal subtype of HGSOC. The identified markers, including PLAU, LAMB1, COL6A1, and TGFB1, warrant further investigation regarding their roles in prognosis, as potential predictors of debulking, and as targets for new therapeutic drugs. Continued research in this field holds the potential to drive advancements in the diagnosis, prognosis, and treatment of ovarian cancer, ultimately leading to improved outcomes for patients.Below is the link to the electronic supplementary material.Supplementary Table-1: Sources and properties of antibodies used in the western blot-ting. Supplementary Table-2: Table containing the list of 57 down (≤ 0.5) accumulated proteins identified by the proteomic analysis of exosomes secreted by the ovarian cancer cell line CaOV3 during EMT. Supplementary Table-3: Table containing the list of 100 up (≥ 1.9) accumulated proteins identified by the proteomic analysis of exosomes secreted by the ovarian cancer cell line CaOV3 during EMT. Supplementary Table 4: Transcriptomic expression (z-Score) of up accumulated proteins with EGF/CTRL ratio ≥ 1.9 in the exosome-enriched fraction during EMT induction in CAOV3 cells, and with higher median expression in the mesenchymal subtypeAdditional file 1:


Prunus avium L.) are among the most important stone fruits in Lebanon. They are harvested between May and July; however, the introduction of new early varieties in low and medium altitudes (500–1000 m) and late varieties in higher altitudes (1800–2200 m) along with postharvest technologies can extend harvesting season. In this study, physicochemical characteristics along with total phenolic content, total anthocyanin content, and antioxidant activity of the most commercial cherry cultivars were evaluated at different altitudes to determine optimum harvesting time. Findings indicated that some varieties, such as “Teliani” and “Irani”, are more significantly impacted by altitude than the other varieties in terms of maturity indices. Duration of fruit development was prolonged with altitude, and in most instances, higher fresh weights and sizes were observed; however, fruit firmness decreased. While total phenolic content  did not significantly vary between varieties, the antioxidant activity (FRAP and DPPH assays) showed the lowest value in “Banni” and the total anthocyanin content showed the highest levels in “Irani” and ”Feraouni” and the lowest in “Mkahal” and “Banni”. Furthermore, total phenolic content and reduction of ferric complex (FRAP) were interestingly influenced by geographical locations, in contrast to total anthocyanin content and radical scavenging activity (DPPH) which were unaffected.Sweet cherries ( Prunus avium L.) is one of the most important non-climacteric fruit crops of the Rosaceae family. It is produced worldwide in temperate climate regions [Sweet cherry , Kaa El Reem high altitude (KER H), Kaa El Reem low altitude (KER L), Barqa (BAR), and Arsal (ARS) between 7 May 2021 and 10 June 2021. It was observed that the 5 berry weight (g) of “Teliani” variety tended to increase with the season. The lowest 5 berry weight (15.14 g) was found in Qousaya on 10 of May 2021 whereas the highest 5 berry weight (35 g) was found in Barqa on 3 June 2021. Fruit diameter (mm) tended to increase between May and June, the lowest fruit diameter values (15.27 mm) were recorded in Qousaya on 7 May 2021 while the highest fruit diameter values (24.49 mm) were recorded in Kaa El Reem (H) on 27 May 2021. Dry matter (%) and sugar content tended to increase with the season and their values almost followed a similar trend. The lowest dry matter (13.18%) was found in Qousaya on 7 May 2021 whereas the highest dry matter (19.26%) was found in Arsal on 10 June 2021. The lowest TSS (11.2 °Brix) was found in Barqa on 27 May 2021 whereas the highest TSS (17 °Brix) was found in Arsal on 10 June 2021. Only titratable acidity (g/L) tended to decrease with harvest date, the lowest TA (6.86 g/L) was found in Barqa on 3 June 2021 whereas the highest TA (16.5 g/L) was found in Qousaya on 7 May 2021. When comparing “Teliani” variety in the same harvest date between two different locations, significant differences were observed on 24 May 2021 for fruit diameter, dry matter, and TA between Kaa El Reem (L) and Kaa El Reem (H), and on 27 May 2021 for fruit diameter and berry weight between Kaa El Reem (H) and Barqa.The “Banni” variety was harvested from Kaa El Reem high altitude and Arsal between 21 June 2021 and 8 July 2021. The 5 berry weight (g) of “Banni” variety tended to increase with the season in the same location, but an important difference was observed between Kaa El Reem (H) and Arsal due to the fact that cherry orchards in Arsal are not irrigated but kept rainfed throughout the season. The lowest 5 berry weight (24.92 g) was found in Arsal on 2 July 2021 whereas the highest 5 berry weight (50.89 g) was found in Kaa El Reem (H) on 24 June 2021. Fruit diameter (mm) did not have high variations in the same location between June and July, the lowest fruit diameter values 19.67 mm were recorded in Arsal on 2 July 2021 while the highest fruit diameter values 26.33 mm were recorded in Kaa El Reem (H) on 21 June 2021. Dry matter (%) and sugar content tended to slightly increase with the season and their values almost followed a similar trend. The lowest dry matter (15.25%) was found in Kaa El Reem (H) on 21 June whereas the highest dry matter (19.54%) was found in Arsal on 2 July 2021. The lowest TSS (14.45 °Brix) was found in Arsal on 2 July 2021 whereas the highest TSS (18.7 °Brix) was found in Kaa El Reem (H) on 28 June 2021. Only titratable acidity (g/L) tended to decrease with harvest date, the lowest TA (6.75 g/L) was found in Arsal on 8 July 2021 whereas the highest TA (9.6 g/L) was found in Kaa El Reem (H) on 21 June 2021.It was observed that the 5 berry weight (g) of the “Irani” variety tended to increase with the season. The lowest 5 berry weight (16.07 g) was found in Qousaya on 24 May 2021 whereas the highest 5 berry weight (51.9 g) was found in Barqa on 5 July 2021. Fruit diameter (mm) tended to increase between May and July, the lowest fruit diameter values (18.53 mm) were recorded in Qousaya on 24 May 2021 while the highest fruit diameter values (28 mm) were recorded in Kaa El Reem (H) on 28 June 2021. Dry matter (%) and sugar content tended to increase with the season and their values almost followed a similar trend. The lowest dry matter (16.31%) was found in Qousaya on 24 May 2021 whereas the highest dry matter (25%) was found in Kaa El Reem (H) on 14 June 2021. The lowest TSS (13.49 °Brix) was found in Qousaya on 24 May 2021 whereas the highest TSS (23.75 °Brix) was found in Kaa El Reem (H) on 28 June 2021.Only titratable acidity (g/L) tended to decrease with harvest date, the lowest TA (8.95 g/L) was found in Barqa on 24 June 2021 whereas the highest TA (14.28 g/L) was found in Qousaya on 27 May 2021. Significant differences were shown between locations when comparing the maturity indices of the “Irani” variety at the same harvest date. It was observed that the 5 berry weight (g) of “Feraouni” variety tended to increase with the season. The lowest 5 berry weight (19.5 g) was found in Qousaya on 8 May 2021 whereas the highest 5 berry weight (56.24 g) was found in Barqa on 24 June 2021. Fruit diameter (mm) tended to increase between May and July, the lowest fruit diameter values (17.96 mm) were recorded in Arsal on 8 July 2021 while the highest fruit diameter values (27.63 mm) were recorded in Barqa on 28 June 2021. Dry matter (%) and sugar content tended to increase with the season and their values almost followed a similar trend. The lowest dry matter (14.9%) was found in Arsal on 8 July 2021 whereas the highest dry matter (25.33%) was found in Qousaya on 3 June 2021. The lowest TSS (11.38 °Brix) was found in Barqa on 17 June 2021 whereas the highest TSS (20.79 °Brix) was found in Kaa El Reem (H) on 28 June 2021. Only titratable acidity (g/L) tended to decrease with harvest date, the lowest TA (9.63 g/L) was found in Barqa on 17 June 2021 whereas the highest TA (16.17 g/L) was found in Qousaya on 27 May 2021.According to the Radar analysis presented in Total soluble solids values for all the studied cherry varieties in all locations ranged between 11.21 and 23.75 °Brix. The highest average TSS value was found in “Skeena” (18.39 °Brix) and the lowest average TSS value was found in “Teliani” cherries (13.19 °Brix). As for locations, Kaa El Reem (H) had the highest average TSS (17.23 °Brix) and Kaa El Reem (L) had the lowest average TSS (14.87 °Brix). Initial pH values for all the studied cherry varieties in all locations ranged between 2.92 and 3.64. The highest average ipH value was found in “Teliani” (3.41) and the lowest average ipH value was found in “Feraouni” cherries (3.17). As for locations, Arsal had the highest average ipH (3.35) and Qousaya had the lowest average ipH (3.12).The 5 Berry Weight values for all the studied cherry varieties in all locations ranged between 15.14 and 56.24 g. The highest average 5 berry weight value was found in “Skeena” (49.86 g) and the lowest average value was found in “Teliani” cherries (26.68 g). As for locations, Barqa had the highest average (44.32 g) and Qousaya had the lowest average (22.88 g).Fruit diameter values for all the studied cherry varieties in all locations ranged between 15.27 and 28 mm. The highest average diameter value was found in “Skeena” (26.73 mm) and the lowest average diameter value was found in “Teliani” cherries (21.15 mm). As for locations, Barqa had the highest average diameter (25.78 mm) and Qousaya had the lowest average diameter (19.68 mm). Dry matter values for all the studied cherry varieties in all locations ranged between 13.18 and 25.33%. The highest average DM value was found in “Irani” (20.09%) and the lowest average DM value was found in “Teliani” cherries (15.94%). As for locations, Qousaya had the highest average DM and Arsal and Barqa had the lowest average DM (17.33%).Firmness with skin values for all the studied cherry varieties in all locations ranged between 0.53 and 3.83 KgF. The highest average FWS value was found in “Feraouni” (1.38 KgF) and the lowest average FWS value was found in ”Banni” cherries (1.1 KgF). As for locations, Qousaya had the highest average FWS (1.81 KgF) and Kaa El Reem (H) had the lowest average FWS (1.09 KgF). The firmness with skin (FWS) measurements fell between 0.53 and 3.83 KgF. The “Feraouni” cherries had the highest average FWS value at 1.38 KgF, while the “Banni” cherries had the lowest average FWS value at 1.1 KgF. Among the locations, Qousaya had the highest average FWS at 1.81 KgF, whereas Kaa El Reem (H) had the lowest average FWS at 1.09 KgF.Analysis of fruit firmness revealed a high variation of values inside the same variety, as per 2 = 0.84) was observed only between the 5 berry weight (g) and the fruit diameter (mm) (A high positive correlation (Rter (mm) .Based on “Banni”, “Feraouni”, “Irani”, and “Mkahal” cherry varieties were tested for phytochemical composition . Total pAnalysis of total phenolic content (GAE), DPPH, TEAC and FRAP the evaluated cherry varieties regardless their harvested locations revealed that there was no significant difference for total phenolic content (GAE) in “Banni”, “Feraouni”, “Irani”, and “Mkahal” varieties . DPPH inSweet cherry growers rely on important characteristics that offer valuable information regarding fruit maturity such as total soluble solids, titratable acidity, and fruit weight .According to Pérez-Sánchez et al. , fruit fWith respect to the total soluble solid ratio for sweet cherries, for commercial purposes, minimum levels were set. Palou  realizedThe tested Lebanese cherry cultivars also differed in their titration acidities (TA). “Mkahal” (8 g/L) had the lower levels followed by “Banni” (8.7 g/L), “Teliani” (9.05 g/L), “Skeena” (9.5 g/L), “Irani” (10.8 g/L), and “Feraouni” (12 g/L). According to Szpadzik et al. , malic aAs for dry matter, “Teliani” (15.94%) had the lower levels followed by “Mkahal” (16.92%), “Banni” 17.28%), “Skeena” (18.7%), “Feraouni” (19.32%) and “Irani” (20.09%). As for fruit diameter, “Teliani” (21.15 mm) had the lower levels followed by “Mkahal” 22.8 mm), “Banni” (22.88 mm), “Feraouni” 23.22 mm), “Irani” 24.33 mm) and “Skeena” 26.73 mm). As for 5 berry weight, “Teliani” (26.68 g) had the lower levels followed by “Mkahal” (35.11 g), “Feraouni” (36 g), “Banni” (36.81 g), “Irani” (37.33 g), and “Skeena” (49.86 g). The weight and size of cherry fruits are the main characteristics that control the commercial value of this fruit. Consumers state that fruits of a larger size and darker color are more appealing [.8 mm, “B.22 mm, “.33 mm an.73 mm. A%, “SkeenRegarding the phytochemical composition, cherries are known to possess high levels of antioxidants, which are beneficial for human health. Gallic acid, DPPH , TEAC , FRAP (Ferric Reducing Antioxidant Power), and total anthocyanins are some of the commonly used parameters to measure antioxidant activity in fruits. El Baji et al.  carried For instance, a study by Slatnar et al.  investigAnother study by Zhang et al.  analyzedCrataegus spp.) and sandal strawberry tree fruit had higher levels of total phenolic compounds and antioxidant activity than the dehydrated ones. They also found a linear correlation between the total phenolic content and antioxidant values of the samples.The total phenolic compounds and antioxidant activity can be affected by various factors, including the dehydration process. In their studies conducted in 2022 and 2023, Özcan et al. ,34 discoHandpicked cherry berries from commercial Lebanese orchards situated in different locations including Arsal (2080 m), Qousaya (1130 m), Kaa El Reem (1280 m and 1600 m), and Barqa (1930 and 1980 m), as outlined in Recording the weight of every 5 fruits separately, for 6 repetitions of 5 fruits per tree.Conducting colorimetric measurements of 30 fruits per tree using the AgroColor colorimeter .Measuring the diameter of 30 fruits per tree using a caliper.Determining the firmness of 30 fruits per tree using a QA FT 327 Fruit Pressure Tester , equipped with a 3-mm tip, and expressing the values in (KgF).Dry matter content of the cherry fruits, kernels from 12 fruits were removed, and 6 repetitions of 2 fruits per tree were weighed before and after being dried in an oven at 65 °C for 36 h, until reaching a constant weight. The results were expressed as a percentage of the original weight and recorded as an average of six individual values per tree.To measure the total soluble solids (TSS) of the cherry fruits, the remaining 18 fruits were blended into juice and tested for TSS expressed as a degree Brix by placing one or two drops of the juice on the prism of a digital Atago PAL-1 refractometer.The initial pH of the juice was also recorded using a HANNA HI2211 pH meter.Titratable acidity: 5 mL of the juice was diluted with 95 mL of dH2O to measure the pH using a HANNA HI2211 pH meter. The titratable acidity was conducted using 0.1 M NaOH until reaching a pH of 8.1. Titratable acidity was calculated as the number of milliliters of NaOH used multiplied by an appropriate factor using this equation (X*75*0.1)/5)*100, where X is the amount of NaOH used, 75 is the tartaric acid conversion factor.Several measurements were conducted on cherry fruits and various fruit parameters were assessed. The measurements included:w/v) cherry juice solution in a 96-well microplate according to the manufacturer’s instructions. Each sample and standard was tested in triplicate and repeated three times. Gallic (GAE) acid was used as the reference standard and results were expressed as µg of gallic acid equivalent per ml of solution (GAE µg/mL). Absorbance was read at 700 nm at 37 °C.Total phenolic content: Total phenolic content was determined with a Folin Ciocâlteu Phenolic Content Quantification Assay Kit  in a 20% (Ferric Reducing Antioxidant Power Assay: The ferric ion reducing antioxidant power (FRAP) was determined using a standardized capacity kit . The reduction of the ferric complex by the extracts at an acidic pH was quantified. The diluted sample (10 µL) was mixed with 220 µL of FRAP working solution and left to react for 4 min. The absorbance was then measured using a microplate reader at 593 nm. The antioxidant activity was expressed as µM of iron(II) equivalent (µM iron (II)).DPPH Radical Scavenging Assay: DPPH  is a stable free radical that can be used to measure the radical scavenging activity of antioxidants. Measurements of DPPH radical scavenging activity were performed using a commercial kit, following the manufacturer’s instructions. Briefly, samples were appropriately diluted in DMSO and mixed with the DPPH solution provided by the kit. The total antioxidant capacity (TAC) was determined by measuring absorbance at 517 nm through a multimode microplate reader , and calculating the corresponding percentage of the inhibition of the radical DPPH as reported in the kit instructions. The DPPH radical scavenging activity of sample was expressed as Trolox equivalent antioxidant capacity .Anthocyanins: Total anthocyanin content was measured using the BQC kit according to the manufacturer’s recommendations . A measure of 20 μL of cherry extracts (10 mg/mL) was mixed with 220 μL of Reagent A or 220 μL of Reagent B in 96-well clear bottom plates. Then, the plates were shaken at 200 rpm, left for 10 min, and the absorbance measured at 510 and 700 nm using a multimode microplate reader . AC values expressed as the means of 3 replicate measurements.t-tests and one-way ANOVA tests. Differences were considered statistically significant for p-values < 0.05 using RStudio statistical software. Radar analysis was performed over all harvesting dates to observe the clustering behavior of the varieties and correlations between maturity indices. Shapiro–Wilk normality tests and studentized residual plots were used to test error assumptions of variance analysis, including random, homogenous, and normal distribution of error. Statistical comparison of maturity indices under different locations by variety was performed using one-way ANOVA parametric test followed by Student–Newman–Keuls (SNK) post hoc test. As a non-parametric alternative to ANOVA, the Kruskal–Wallis test was used followed by Dunn’s test. Differences between locations for the same variety were considered statistically significant for p-values < 0.05 using R Studio statistical software.Statistical analysis was undertaken when samples were obtained from various sites on the same date for the same variety. After the data were entered and cleaned from extreme values, statistical comparison of all parameters was performed using In conclusion, the location where sweet cherries are grown can have a significant impact on their antioxidant capacity and phenolic composition. Therefore, it is important to consider the origin of sweet cherries when evaluating their health benefits and nutritional value. Further research should aim to study cultivar-specific strategies that can improve fruit quality and the level of health-related compounds. The interaction of genetics, agricultural practices, rootstocks, environmental factors, growth regulators, storage techniques, and new preservation technologies has a great impact on final fruit quality and, thus, needs to be optimized.


Pelotomaculum thermopropionicum is performed under a thermodynamic limit. The most energetically unfavorable reaction in the propionate oxidation pathway is succinate oxidation. Based on previous genomic and transcriptomic analyses, succinate oxidation in P. thermopropionicum under propionate-oxidizing conditions is conducted by the membrane-bound forms of two succinate dehydrogenases (SDHs). We herein examined the activity of SDH, the mechanisms underlying the succinate oxidation reaction in P. thermopropionicum, and the importance of the protein sequences of related genes. SDH activity was highly localized to the membrane fraction. An analysis of the soluble fraction revealed that fumarate reductase received electrons from NADH, suggesting the involvement of membrane-bound SDH in propionate oxidation. We utilized an uncoupler and inhibitors of adenosine triphosphate (ATP) synthase and membrane-bound SDH to investigate whether the membrane potential of P. thermopropionicum supports propionate oxidation alongside hydrogen production. These chemicals inhibited hydrogen production, indicating that membrane-bound SDH requires a membrane potential for succinate oxidation, and this membrane potential is maintained by ATP synthase. In addition, the phylogenetic distribution of the flavin adenine dinucleotide‐binding subunit and conserved amino acid sequences of the cytochrome b subunit of SDHs in propionate-oxidizing bacteria suggests that membrane-bound SDHs possess specific conserved amino acid residues that are strongly associated with efficient succinate oxidation in syntrophic propionate-oxidizing bacteria.Propionate oxidation in  It conv species . In addiacterium . However of SDHs   was routinely grown on 18 mM fumarate or pyruvate in 50 mL WY medium at 55°C in a 120-mL serum vial with a butyl rubber seal. WY medium containing 0.01% yeast extract in W medium was prepared as previously described . Regarding the direct inoculation, the preculture (5 mL) was directly inoculated into new media. In the wash inoculation, the preculture was washed as follows: cells were collected from 50 mL of the preculture via centrifugation. Cells were then suspended in 1 mL WY medium after being washed with fresh WY medium three times. One hundred microliters of the cell suspension was inoculated into fresh 50 mL WY medium with 18 mM propionate in a butyl rubber-sealed vial. The vial was incubated at 55°C for ~40 d, and hydrogen was periodically measured in the headspace. When a constant hydrogen production rate was observed, the headspace was substituted with N2:CO2=80:20 gas for 3 min in a process known as gas exchange to remove existing hydrogen and reduce oxygen contamination, and the vial was then incubated at 55°C. One hundred microliters of each chemical reagent solution was added via a syringe (Terumo). Carbonyl cyanide m-chlorophenylhydrazone (CCCP), 2-thenoyltrifluoroacetone (TTFA), and N,N-dicyclohexylcarbodiimide (DCCD) were dissolved in pyridine. The additive cofactors were dissolved in water and sterilized by filtration.600 value was >0.15, cells were collected via centrifugation at 5,000×g at 4°C for 10 min during the stationary phase. The cell pellet was centrifuged again after being washed with saline containing 8.5 mg L–1 NaCl. The pellet was suspended in 10 mL of 10 mM potassium phosphate buffer  and subjected to 16,000 psi of pressure in a French press (American Instrument Company). Debris was removed via centrifugation at 8,000×g at 4°C for 15 min, and the supernatant was ultracentrifuged at 100,000×g at 4°C for 60 min using an ultracentrifuge . The resulting precipitate was homogenized in 10 mL of 10 mM KPB and used as the membrane fraction. The collected supernatant was dialyzed against 1 L of 10 mM KPB at 4°C every 6 h. The treated solution was used as a soluble fraction.After an incubation at 55°C for several d when the OD–1 cm–1 was considered to be the molecular extinction coefficient of DCIP  oxidoreductase activity was measured at 275 nm, and we considered 12.25 mM–1 cm–1 to be the molecular extinction coefficient of Q1 . Using a spectrophotometer, routine analyses were conducted at room temperature using 3-mL plastic or 1-mL quartz cuvettes . Succinate:phenazine methosulfate (PMS)/2,6-dichloroindophenol (DCIP) oxidoreductase activity was measured at 600 nm, 14.52 mMnt of Q1 ; one uni–1. A calibration curve was produced using standard H2 gas (GL Sciences).The gas phase of the cultured vial or bottle was collected using a gas-tight syringe (Hamilton) and applied to a gas chromatography device  equipped with a thermal conductivity detector (TCD) and a 2×3 mm stainless steel column containing Unibeads C (60/80 mesh) (GL Science). The temperature of the injection port and detector was 150°C, and that of the column was 145°C. The TCD was set to a current of 60 mA, and the flow rate of the carrier gas argon was 30 mL minnih.gov/genomes/refseq/). To detect the homologous sequence of SDH/fumarate reductase (FDR), flavoprotein subunit A, we performed a BLASTP search (Escherichia coli BW25113 (SdhA: accession no. AIN31199) and P. thermopropionicum SI (Sdh1A: BAF59198 and Sdh2A: BAF59672) as the query. The homologous set was selected by BLASTP based on the criteria of an E-value cut-off of 1e-5 and a minimum aligned sequence length coverage of 70% of a query and hit sequence. All hits from each query were collected, and the merged unique sequence data set was used to build the phylogenetic tree. The input sequence was aligned using MUSCLE 3.8.31 at the amino acid sequence level and used for phylogenetic construction  FTP website  and UniProt (https://www.uniprot.org) databases.To elucidate the structure of the SDH/FDR gene cluster, 10 genes encoded in the region surrounding each hit were collected. Five of these genes were each encoded in the upstream and downstream regions. Therefore, each hit along with 10 surrounding genes were defined as candidates for the structure of the gene r of 1.2 . By usinP. thermopropionicum SI possesses two types of SDHs, designated as SDH1 and SDH2   were similar and also that the most well-known FAD-binding residue His43 (menaquinol:fumarate oxidoreductase (QFR) as succinate and fumarate, respectively (Pelotomaculum (The importance of membrane-associated SDH in th SdhD) . To exam clade 7 . Althougroxidans . Conservue His43 A. The eiue His43 A. Gln omaculum A.cluster and cytochrome b subunits and the phylogeny of the flavoprotein subunit by summarizing the structures of the cluster of protein homologs comprising SDH/FRD based on the phylogenetic tree of the flavoprotein subunit  was highly conserved   and S. fumaroxidans    were pre Glu196) . The E-p Glu196) . These fD. gigas B. Furtheshinckii B, suggesP. thermopropionicum, the key oxidizing enzyme directly related to propionate hydrogen production, localizes to the membrane and that the enzyme complex responsible needs to contain the membrane-integrated subunit. A sequence analysis predicted that SDH (SDH1) possesses a quinone pocket in SdhC , coenzyme F420 hydrogenase/dehydrogenase beta subunit, C terminus (IPR007525), and 4Fe-4S ferredoxin-type iron-sulfur binding domain (IPR017896). However, an additional subunit that oxidizes NADH and transfers electrons to FRD may be required. In the genome of P. thermopropionicum, several genes exhibit possible NADH-oxidizing domains, such as NAD_binding_1 (Pfam No. PF00175), oxidized_FMN (PF00724), and Complex1_51K (PF01512). These domains containing genes include PTH_1405 (NAD_binding_1); PTH_0267, PTH_0595, and PTH_0596 (Oxidored_FMN); PTH_2011, PTH_1378, and PTH_2648 (Complex1_51K) , which lacks heme groups and a predicted membrane-integrated domain cytoplasmic b-like  . The appP. thermopropionicum required an ATP synthase-maintained membrane potential for succinate oxidation. This was necessary because propionate hydrogen production by P. thermopropionicum required a membrane potential , indicating that a membrane potential may also be required to drive the HYD4 reaction.The membrane-bound SDH of otential A, ATP syotential B, and quotential C. These  wolinii . TTFA, w wolinii , partialactivity , suggestactivity . AdditioBacillus subtilis (Desulfovibrio species (Bacillus licheniformis (b subunit) have been proposed in SQR(SDH) of B. licheniformis and QFR(FRD) of W. succinogenes  and Wolinella (27% identity). Subunit C of D. gigas QFR has been suggested to utilize the E-pathway in the reversible reaction of quinol oxidation  Membrane Potential-requiring Succinate Dehydrogenase Constitutes the Key to Propionate Oxidation and Is Unique to Syntrophic Propionate-oxidizing Bacteria. https://doi.org/10.1264/jsme2.ME22111Supplementary Material 1Supplementary Material 2


Grapevine development and ripening are complex processes that involve several biochemical pathways, including fatty acid and lipid metabolism. Fatty acids are essential components of lipids, which play crucial roles in fruit maturation and flavor development. However, the dynamics of fatty acid metabolism in grape flowers and berries are poorly understood. In this study, we present those dynamics and investigate the mechanisms of fatty acid homeostasis on ‘Thompson Seedless’ berries using metabolomic and proteomic analyses. Low-polar metabolite profiling indicated a higher abundance of fatty acids at the pre-flowering and pre-veraison stages. Proteomic analyses revealed that grape flowers and berries display unique profiles of proteins involved in fatty acid biosynthesis, triacylglycerol assembly, fatty acid β-oxidation, and lipid signaling. These findings show, for the first time, that fatty acid metabolism also plays an important role in the development of non-oil-rich tissues, opening new perspectives about lipid function and its relation to berry quality. Vitis vinifera L.) is one of the most economically important fruit crops cultivated globally. There are more than 10,000 productive cultivars in the world, including table grapes and wine grapes [The grapevine , phospholipids, and sterols . De novoLipids are precursors of signaling molecules, such as jasmonates, that regulate stress responses and defense mechanisms during grape berry ripening ,30. PlanAs a continuation of previous work focused on grape berry central carbon metabolism , the aimTamarix dioica and Rosa damascena flowers, providing aroma traits when full bloom is achieved [Grape bunches previously used for polar metabolite profiling , were usachieved ,36. Tocoachieved , have beachieved . For fruit stages, most of the low-polar metabolites accumulated in the early stage of berry development pre-veraison D. The acIn addition, a univariate analysis of the main free fatty acids detected by GC-MS and lipid-derived fatty acids by GC-FID was carried out. GC-MS analysis showed that oleate was highly accumulated during flowering A. On theFor fruit stages, at pre-veraison, we observed higher concentrations of oleate, linolenate, methyl linolenate, methyl linolate, methyl linoelaidic acid, methyl palmitate, and glyceryl palmitate via GC-MS B. The faA proteomic approach was performed by liquid chromatography with tandem mass spectrometry (LC-MS/MS) to better understand the dynamics of lipid metabolism during grapevine flowering and fruit development. The proteomic dataset obtained was previously used for pathway analysis and reconstruction of grapevine central carbon metabolism . For thiFor fruit stages, it was observed that a significant group of proteins were accumulated at the harvest stage, and an elevated number of these proteins were also increased at the veraison stage E. In addFatty acid biosynthesis requires several enzymes and occurs within the chloroplast of plant cells . A totalKAS, KAR, HAD, and EAR genes continuously decreases until grape berries reach maturity. Interestingly, we found proteins that shared this expression/abundance behavior and other proteins that exhibited an accumulation pattern throughout the ripening of grape berries. This behavior could be explained by the fact that fatty acids and their derivatives are involved in the signaling of metabolic pathways related to the ripening process of grape berries [At fruit stages, 27.8% (10/36) of the enzymes were significantly different, and half of these proteins (5/10) were found to be more abundant at the pre-veraison stage, including EAR1, EAR3, OAR7, OAS1, and OAS2. At veraison, only the enzyme EAR3 was observed to be more abundant. For harvest stage, ACC5, ACC6, KAR1, and OAR8 were found to have accumulated B. Overal berries ,55.Camellia reticulata, transcriptomic analysis showed the same accumulation pattern observed in our data for DGAT1, DGAT2, PDAT1, and PDAT2 [Related to TAG biosynthesis, little is known about this metabolic process in grapevine flower development. During flowering, some of the fatty acids pool are used for the synthesis of volatile compounds that confer the fragrance of the flowers ,56. Howend PDAT2 .GPAT- and DGAT-transcript expression decreased across ripening [At fruit stages, 14.3% (3/21) of the enzymes were significantly different, and GPAT1 was found upregulated at the pre-veraison stage, while GK and DGAT1 were observed accumulated at veraison B. In agrripening . In addiripening . In addiripening . This meFree fatty acids derived from TAGs are mainly metabolized within the peroxisome/glyoxysome via β-oxidation . A totalAt fruit stages, 27.3% (9/33) of the enzymes showed a significantly different accumulation, and most of these proteins (6/9) were found to be more abundant at the harvest stage, including LACS4, LACS6, HADH1, HADH2, HADH4, and HADH5. For the pre-veraison stage, ACX1 and ACX3 were found to have accumulated. At veraison, only the enzyme ECH1 was observed to be more abundant B. Our fiS-lipoxygenases , allene oxide cyclase (AOC), and hydroperoxide lyases (HPL1 and HPL2) (Z)-3-hexenal produced by hydroperoxide lyase activity has been reported to be highly concentrated at full bloom in grapevines cv. ‘Chardonnay’, displaying a correlation with the HPL protein accumulation detected during flowering [PLA2-16 and PLA2-17 expression [Plant lipid signaling represents a dynamic system that orchestrates a wide range of cellular processes. From structural components of membranes to secondary messengers and regulators of stress responses, lipids play integral roles in plant growth, development, and adaptation to changing environments ,64. Lipind HPL2) A. Duringlowering ,69. Phoslowering . Moreovepression ,72. In apression . HPL accumulation close to veraison [PLDα exhibited an abundance reduction in grape berries cv. ‘Noble’ [LOX1, two LOX2, and a LOX gene, a reduction in the expression was reported, pointing to a highly dynamic spatiotemporal lipoxygenase expression pattern, as observed in our findings [At fruit stages, 33.3% 18/54) of the proteins exhibited a significantly different accumulation, and most of these proteins (10/18) were found to be more abundant at the harvest stage, including lipoxygenases , 12-oxophytodienoate reductases , and phospholipases . For veraison stage, PLA2-1, PLA2-2, PLA2-3, PLA2-17, and PLDα-5 were found to have accumulated. At pre-veraison, the enzymes AOC, PLA2-8, and PLDδ-4 were observed to be more abundant B. Jasmonveraison . Hydrope ‘Noble’ . Moreovefindings ,54. of the pVitis vinifera L.) inflorescences and bunches of the cv. ‘Thompson Seedless’ were collected and phenotypically characterized as previously described by Olmedo et al. [Grape  were added, and the samples were vigorously shaken, followed by centrifugation at 4800× g for 10 min at 4 °C. The upper phase was discarded, and 2 mL of methanol:water (1:1) was added. Samples were vortexed and incubated at 4 °C overnight. After incubation, samples were centrifugated at 4800× g for 10 min at 4 °C. The upper polar phase was discarded, and the lower chloroform phase was evaporated using gaseous nitrogen. Then, 0.2 mL of N-trimethylsilyl-N-methyl trifluoroacetamide (MSTFA) was added to the samples, followed by incubation at 120 rpm for 30 min at 37 °C. Samples were collected and transferred to GC vials. The vials were capped and stored at −80 °C until further GC analysis.Extraction and derivatization were performed according to Lytovchenko et al.  with mod−1, and a 25:1 split ratio was used. The initial temperature of the oven was 120 °C for 1 min; then, it was increased to 300 °C (5 °C each 1 min) and maintained for 15 min. The ionization source and quadrupole temperatures were 230 °C and 150 °C, respectively. Mass spectra were obtained in a 50 to 600 m/z interval with a scan rate of 2.66 cycles per second. Metabolites were identified using MassHunter Quantitative Analysis software version B.07.01  and the NIST Library14. Metabolites were reported based on their relative quantification. QC samples composed of equal amounts of all samples were run every 10 samples. To obtain a relative response of each compound, the peak area data were corrected using the peak area of phenyl β-D-glucopyranoside , the sample fresh weight, and a quality control (QC) sample representative of all samples. Data were analyzed by using relative concentration tables in the MetaboAnalyst 5.0 software. The software indicated that a total of 0% of missing values were detected. The variables were mean-centered and weighted using standard deviations to assign an equal variance. The metabolites were reported as previously described [The low-polar metabolites were determined by injecting 1 µL of the prepared samples into an Agilent 7890B gas chromatograph equipped with a 5977A single quadrupole mass spectrometer, an electron impact ionization source, a PAL3 autosampler, and a 30 m × 0.25 mm × 0.25 µm DB-5ms column . The injector and interface temperatures were 220 °C and 280 °C, respectively. The helium flow rate was 1 mL minescribed  in Table2SO4 was added. The tubes were then mixed by inversion and incubated again in the water bath for 1.5 h at 55 °C with shaking every 30 min. After fatty acid methyl ester (FAME) synthesis, the tubes were cooled in a cold tap water bath. Then, 0.5 mL of hexane and 0.01 mL of internal standard  were added in a proportion of 0.97 mL of hexane and 0.03 mL of the internal standard. The tubes were vortexed for 2 min and centrifuged for 10 min at 17,000× g. The hexane phase (upper phase) containing the FAME was collected and transferred to GC vials. The vials were capped and stored at −80 °C until further GC analysis.The extraction was performed using a previous method with some modifications . Briefly−1. The column heating ramp was initially set at 130 °C, held for 5 min, followed by an increase from 130 °C to 180 °C at 5 °C per min, held at 180 °C for 10 min, increased from 180 °C to 240 °C at 3 °C per min, and held at 240 °C for 13 min. For fatty acid identification and quantification, the retention times were compared to the external analytical standards. The results were expressed as g of fatty acid kg−1 dry weight (DW). The fatty acid composition of the FAME fraction was determined in a gas chromatograph  equipped with a capillary column . The injector temperature was set to 220 °C; flame ionization detector (FID) at 280 °C. Helium was used as carrier gas with the flow at 1 mL minw/v) dithiothreitol , 1 mM phenylmethylsulfonyl fluoride , and 30% (w/v) sucrose, and immediately vortexed. Then, 0.5 mL of tris-equilibrated phenol solution was added, and the samples were homogenized for 10 min at 4 °C and centrifuged at 10,000× g for 10 min at 4 °C. The phenolic phase was collected and re-extracted by adding 0.5 mL of extraction buffer and centrifuged again. The collected phenolic phase was incubated overnight at −20 °C to induce protein precipitation with the addition of 1 mL of 0.1 M ammonium acetate in methanol. After incubation, samples were centrifuged at 17,000× g for 30 min at 4 °C, and the supernatant was discarded. Then, the pellet was rinsed using 0.2% (w/v) DTT in cold acetone, incubated at −20 °C for 1 h, and centrifuged again. The pellet obtained was air-dried, resuspended in 0.1 mL of lysis buffer , and dissolved by vigorous agitation. Protein quantification was carried out with a Bio-Rad Protein Assay , according to the manufacturer’s instructions, and using bovine serum albumin as the protein standard. Then, 0.02 mg of proteins were incubated for 15 min with DTT solution up to a final concentration of 20 mM. The samples were incubated for 30 min in the dark with iodoacetamide up to a final concentration of 50 mM and diluted using 0.15 M ammonium bicarbonate. The digestion of proteins was carried out by adding trypsin (0.2 mg mL−1) and incubated overnight at 37 °C. Peptides were acidified with trifluoroacetic acid  solution  and purified using Pierce C18 spin columns . The solvent was evaporated by Speed-Vac evaporation , and the pellet was dissolved in 0.1 M ammonium formate.Protein extraction and digestion were performed as previously described with some modifications . Samplesv/v) formic acid , in water and solvent (B), 0.08% (v/v) formic acid, in 80% (v/v) acetonitrile , using a linear gradient (0.3 mL min−1) of 0–4% buffer B (80% (v/v) acetonitrile, 0.08% (v/v) formic acid) in 3 min, 4–10% B in 12 min, 10–35% in 20 min, 35–65% in 5 min, 65–95% in 1 min, 95% for 10 min, 95–5% in 1 min, and 5% in 10 min [m/z 200) for the mass range of m/z 400 to 1600 for precursor ions, followed by MS/MS scans of the top ten most intense peaks with 2+, 3+, 4+, and +5 charged ions above a threshold ion count of 16,000 at 17,500 resolution using a normalized collision energy of 25 eV with an isolation window of 3.0 m/z and dynamic exclusion of 10 s. Data were acquired with Xcalibur 3.1.66.10 software . All raw data were converted into mgf files by Proteome Discoverer 1.4  for identification and processed using Mascot 2.2.06  against a Vitis vinifera cv. ‘Cabernet Sauvignon’ clone 08 v1.1–Chromosome scale database [Samples were separated from 0.5 μg of digested material using an Ultimate 3000 ultra-high performance liquid chromatography (UHPLC) system  equipped with an Acclaim PepMap100 C18 pre-column  and a C18 PepMap RSLC column . The mobile phase was composed of solvent (A), 0.1% .Principal component analysis (PCA) was performed on the normalized dataset obtained by GC-MS, GC-FID, and LC-MS/MS using the MetaboAnalyst 5.0 software. A one-way ANOVA with a Fisher’s least significant difference (LSD) post-hoc test was used to compare the means of each metabolite or protein at different phenological stages. The ANOVA was performed using R software version 4.0.2 , with significance set at In this study, our results focused, for the first time, on the dynamics of fatty acid metabolism during flower and table grape berry development. We found that flowers and berries contain unique signatures in low-polar metabolite content, indicating a differential accumulation pattern during grape tissue development. Also, our data showed an overall increased fatty acid biosynthesis at the late stages of flower development and the early stages of berry growth, concomitant with the required lipids by the active cell division rates. In addition, an increased fatty acid catabolism by β-oxidation was found during berry ripening, suggesting an important role for fatty acid metabolism in energy production through berry development. Moreover, higher lipid signaling, closely related to the formation of jasmonate by fatty acid β-oxidation during the late stages of berry ripening, proposes a maturity process accompanied by senescence of the tissue. Finally, this work provides novel information about the role of lipid metabolism in non-oil-rich tissues during grapevine development and ripening, opening new perspectives on and future research outlines into the function of fatty acids in maintaining the homeostasis of energy production during the growth and development of grapevines and their relation to fruit quality.