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Preparative Biochemistry and Biotechnology Publication details, including instructions for authors and subscription information: http://www.tandfonline.com/loi/lpbb20
Optimization of Anticancer Exopolysaccharide Production From Probiotic Lactobacillus Acidophilus by Response Surface Methodology ab
a
b
Venkataraman Deepak , Sureshbabu Ram Kumar Pandian , Shiva. D. Sivasubramaniam , a
a
Hariharan Nellaiah & Krishnan Sundar a
Department of Biotechnology, Kalasalingam University, Krishnankoil, Tamilnadu, India
b
School of Science and Technology, Nottingham Trent University, Nottingham, UK Accepted author version posted online: 01 Apr 2015.
Click for updates To cite this article: Venkataraman Deepak, Sureshbabu Ram Kumar Pandian, Shiva. D. Sivasubramaniam, Hariharan Nellaiah & Krishnan Sundar (2015): Optimization of Anticancer Exopolysaccharide Production From Probiotic Lactobacillus Acidophilus by Response Surface Methodology, Preparative Biochemistry and Biotechnology, DOI: 10.1080/10826068.2015.1031386 To link to this article: http://dx.doi.org/10.1080/10826068.2015.1031386
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Optimization of Anticancer Exopolysaccharide Production from Probiotic Lactobacillus acidophilus by Response Surface Methodology Venkataraman Deepak 1,2, Sureshbabu Ram Kumar Pandian1, Shiva. D. Sivasubramaniam2, Hariharan Nellaiah1, Krishnan Sundar1, 1
Department of Biotechnology, Kalasalingam University, Krishnankoil, Tamilnadu, India 2
School of Science and Technology, Nottingham Trent University, Nottingham, UK
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Corresponding Author Dr. Krishnan Sundar, Department of Biotechnology, Kalasalingam University, Krishnankoil–626126, Tamilnadu, India. Email: [email protected]
Abstract Colorectal cancer (CRC) is one of the leading causes of cancer-related deaths in the Western world. Recently, much attention has been focused on decreasing the risk of CRC by consuming probiotics. In the present study exopolysaccharide (EPS) extracted from Lactobacillus acidophilus was found to inhibit the growth of CaCo2 colon cancer cell line in a dose dependent manner. The experiment was performed in both normoxic and hypoxic conditions and EPS was found to reduce the survival of CaCo2 cell line in both the conditions. qPCR studies demonstrated that EPS treatment up-regulated the expression of Peroxisome Proliferator Activator Receptor–γ (PPAR-γ) in both normoxia and hypoxia conditions, whereas it up-regulated the expression of erythropoietin (EPO) in normoxic condition but there was no significant expression under hypoxic conditions. Hence, the EPS production was optimized by Plackett Burnam design followed by central composite rotatory design. The optimized production of EPS at 24 h was found to be 400 mg/L. During batch cultivation the production peaked at 21st h resulting in an EPS concentration of 597 mg/l.
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Key Words: Exopolysaccharides; Colon cancer; CaCo-2; PPAR- γ; EPO expression, response surface methodology
INTRODUCTION Lactic Acid Bacteria (LAB) have been a source of innumerable health benefits to the human population. Consumption of LAB with food or supplements was found to reduce
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the level of serum cholesterol,[1] and removal of pathogenic bacteria from the intestine,[2] though the main focus of LAB formulations is to balance the microbial population of the intestine.[3] The potential protective influence of LAB against colon cancer is also reported.[4]
Among various LAB, L. acidophilus is part of the intestinal microflora and one of the extensively used non-pathogenic strains for various health benefits.[2] Until recently, Lactobacillus acidophilus has been reported to prevent cancer by binding with the monoamines formed during cooking of meat; and by inactivation of enzymes that produce carcinogens (e.g. β-glucuronidase). EPS are polymers of sugars, which are nothing but long chained polysaccharides. Various LAB have been shown to synthesize EPS.[5] EPS have been shown to enhance taste in food substances,[5] confer immunomodulation with antioxidative effects,[6] and reduce the risk of colon cancer.[4] According to current statistics, colorectal cancer (CRC) has been the third most common type of cancer in men and second in women.[7] Although the incidence of colon cancer is less compared to rectal cancer in India, its numbers are constantly increasing.[8] Recent studies also show that people eating red meat are prone to CRC.[9] Hypoxia -
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environments with low oxygen levels are often encountered in cancer, including colon cancer. The cancer cells multiply faster than the formation of vasculature and often results in hypoxic regions which is resistant to both radiotherapy and chemotherapy. Hypoxia, results in modifications in the expression pattern of various genes, resulting in the persistent proliferation of the cancer cells and also tumor vasculature.[10]
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This report mainly focuses on the determination of anti-proliferative activities of EPS extracted from L. acidophilus. The components were then optimized for maximum production by Plackett-Burman (PB) and Central Composite Rotatable Design (CCRD), followed by batch studies in a fermenter. Response surface methodology (RSM) involves regression analysis and can be used to predict the interaction of various factors involved in optimization, which is not possible with the conventional one-factor-at-a-time method. RSM has been previously used to optimize the production of various enzymes,[11, 12] biopolymers,[13] biomass, [14] oat milk production, [15] and even exopolysaccharides from Lactobacillus delbrukii.[16]
EXPERIMENTAL Culture Lactobacillus acidophilus (10307) was obtained from Microbial Type Culture Collection (MTCC), IMTECH, Chandigarh, India. The subculture was renewed every fortnight in MRS agar (Hi-Media, India), maintained at 4oC and used for experiments.
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Characterization of EPS by FT-IR EPS was essentially produced in MRS medium (37°C, pH 6.5) and extracted by using cold-ethanol method. Initially, the culture was collected and TCA was added to the final concentration of 10%. The mixture was incubated at 4ºC for 3 h and the precipitate was centrifuged and discarded. To the supernatant ice-cold ethanol was added in an equal ratio and incubated at 4ºC overnight. EPS which is formed as a precipitate was collected.
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EPS was then purified by repeatedly dissolving it in distilled water and extraction with cold ethanol. The purified EPS was dialysed and used in further studies.[17] The EPS extracted was dried using a vacuum drier for 24 h and subjected to FT-IR using the KBr pellet method. The pellet was analyzed for FT-IR spectrum using a Fourier Transform IR Spectrometer (Shimadzu, Japan) in the range of 400-4500 cm-1.
Cell line and Treatment conditions CaCo2 cell line, kindly offered by Prof. Stephen Forsythe, Professor, Nottingham Trent University, UK, was maintained in EMEM supplemented with 10% serum. To determine the effect of EPS on CaCo2 cells under normoxic conditions, cells were seeded into a 96 well plate with 1.25 x 103 cells per well and incubated at 37oC in a humidified atmosphere containing 5% CO2. For treatment under hypoxic conditions (2% oxygen), cells were seeded into a 96 well plate with 3 x 103 cells per well and incubated at 37oC in an atmosphere containing 2% oxygen and 5% CO2. Later the cells were treated with various concentrations of EPS and the survival was checked after 48 hr using MTT assay. MTT was added to the media and incubated for 1 h. The formed formazon crystals were
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dissolved using DMSO and the obtained A570 was compared with that of the control.
Real-Time Quantitative PCR studies Real-time quantitative PCR was used to determine the status of mRNAs of two factors PPARγ and EPO. After treating the CaCo2 cells with the toxic concentration of EPS, mRNA was extracted and converted to cDNA by the method prescribed by the
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manufacturer (Superscript™ II Reverse Transcriptase Kit). Obtained cDNA was either used for further studies or stored in 4oC for future use. qPCR reaction mixture with 5 µM of forward and reverse primers, 50 pg of cDNA template, AmpliTaq Gold polymerase and SYBR green PCR master mix (Biorad) was prepared and Real-time qPCR studies were performed. The primer sequences used were PPARγ (Annealing Temp. 54oC) forward 5’–GCTGTGCAGGAGATCACAGA–3’, Reverse 3’GGCTCCATAAAGTCACCAA-5’; EPO (Annealing Temp. 56.1oC) forward 5’GCCAGAGGAACTGTCCAGAG -3’, reverse 3’-CAGGTCATCCTGTCCCTGATP-5’. Each product was amplified for 40 cycles. For normalization of the cycle threshold (Ct) values for each cDNA template, Ct values of three control genes were used namely GAPDH (Glyceraldehyde 3-phosphate dehydrogenase), HGPRT-1 (hypoxanthine guanine phosphoribosyl transferase-1) and TBP-1 (Tat-binding protein-1, a component of 26S proteasome).[18]
Response Surface Methodology Choice of medium components using Plackett-Burman design
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In order to select the significant components responsible for the production of EPS, various nutrients have been checked. The design consisted of 11 components (4 carbon sources, 3 nitrogen sources and 4 Salts) and 12 experiments were performed. The nutrients selected were Glucose, Lactose, Fructose, Sucrose, Peptone, Yeast Extract, Tryptone, MgSO4, CaCl2, K2HPO4 and NaH2PO4. The pH was maintained at 6.5 and temperature at 37oC. The experimental design, with coded values, is shown in Table 1.
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After 24 h, EPS was extracted and the response was analyzed. From the response the components that significantly affected the production of EPS were selected and used for CCRD.
Effect of pH on the production of EPS In order to determine the pH at which the production was optimum, the pH of the media was varied from 4 -9 at the interval of 0.5 and effect was determined.
Effect of time on production of EPS In order to determine the effect of time on the production of EPS, the bacterial culture was incubated for 36 h. The EPS was extracted every 6 h and the amount of EPS produced was determined.
Effect of Temperature on the production of EPS In order to assess the effect of temperature on the production of EPS, the bacterial culture was incubated at various temperatures ranging from 20°C – 50°C and production of EPS
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was analyzed.
Effect of carbon source on the production of EPS In order to determine the concentration of carbon source at which the EPS production is enhanced the concentration of carbon source is varied from 1% to 5%.
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After 24 h, EPS produced was extracted and quantified.
Effect of nitrogen source on the production of EPS In order to determine the concentration of nitrogen source at which the EPS production is enhanced the concentration of nitrogen source is varied from 0.25% to1.5%. After 24 h, EPS produced was extracted and quantified.
Medium optimization by Central Composite Rotary Design After the variables for the production of EPS were screened, a Central Composite Rotatable Design was performed to optimize the media and to obtain a quadratic model for the production of EPS by L. acidophilus. The model consists of various trials with quadratic points and central points with the production of desired product (EPS production) as response. The design of experiments was generated using Design Expert software (Version 8.0 Trial, Stat-Ease, Inc., Minneapolis, USA). The design consists of 30 experiments with 6 trails for the central compositions replications, 8 axial trials and 16 trials for factorial design. The experiment consisted of four different variables A – Sucrose; B – Yeast Extract; C – A mixture of Salts (KH2PO4 & MgSO4 (1:1)); D – NaCl at 5 coded levels (-α, -1, 0, +1, +α) as shown in Table 2. The actual levels of the variables
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for the CCRD design were determined by the PB design and the reference to the onefactor-at-a-time determination of media composition. The impact of each of the four variables on the production of product (EPS) is given by second-order polynomial equation given by
Y= B0 + B1 X1 + B2 X2 + B3 X3 + B4 X4 + B12 X1 X2 + B13 X1 X3 + B14 X1 X4 + B23 X2 X3
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+ B24 X2 X4 + B34 X3 X4 + B11 X12 + B22X22+B33X32+B44X42
Where X1, X2, X3, X4 are input variables which here corresponds to A – Sucrose; B – Yeast Extract; C – A mixture of Salts (KH2PO4 & MgSO4 (1:1)); D – NaCl respectively. The coefficients B corresponds to linear, cross-product and quadratic coefficients. The experiment was performed in a media volume of 100 ml at pH 6.0 and 37°C.
Fermenter Studies The efficacy of the CCRD-optimized medium to produce EPS was determined in batch fermentation using a 3L bench-top fermenter (Bioengineering, KLF 2000, Switzerland). Initially, the medium components were sterilized in situ and inoculated with 10% (v/v) of seed. The conditions maintained were 30°C, 200 rpm, pH 6.0 and aerated at the rate of 1.67 vvm for 24 h. Samples were withdrawn every 3 h and the EPS was extracted.
Statistical Methods Analysis was performed through Graphpad Prism 6 software. For MTT assay and RT qPCR studies, Student’s ‘t’ test was used for the analysis and **p F) < 0.00001) indicates that the model is highly significant. The fitness of the model was given by the R-squared value which is 0.96. This shows that the variation in the production of EPS is 96% attributed to the variables and only less than 4% could not be explained by the model. The predicted R-squared value of 0.8100 is in reasonable agreement with the “Adj R-Squared” vaue of 0.9275 which confirms the significance of the model.The statistically insignificant lack of fit value of ((Prob>F) = 2.62 shows that the model is adequate for the prediction of the EPS production in the range of the nutrients employed. Coeffecient of variation was found to be 7.23% which is low and makes the model precise and reliable. The significane of the values is given in Table 5. Higher the value of t-test and lower the p value shows that the coefficient terms are highly significant. The significant variables
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from this design include A, B, C, D, A2, B2, C2 and D2. Therefore eliminating the insignificant terms
Y = 40.00 + 3.38 * A+ 1.46 * B + 0.96 * C +1.37 * D - 3.41 * A2 +3.03 * B2- 2.78 * C2- 5.53 * D2 (Eq. 2) ‘‘Adeq Precision” measures the signal (response)-to-noise (deviation) ratio, a
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ratio greater than 4 being desirable. In the present study involving medium optimization for EPS production, the ratio of 9.265 indicated an adequate signal.
The 3D-graphs obtained are shown in Figure 5. The 3D plot obtained is the graphical representation of the obtained regression equation. The graphs are drawn based on the effect of two variables on the EPS production by keeping the other two variables as zero. Fig. 5A, 5B, 5C, 5D, 5E and 5F show the interaction of Sucrose vs Yeast extract; Sucrose vs salts; Sucrose vs NaCl; Yeast extract vs salts; Yeast extract with NaCl; Salts vs NaCl respectively. The final optimized concentration of EPS from CCRD was 400 mg/L.
Validation of the model The production of exopolysaccharides was validated using the model proposed. The results obtained from the experiment were similar to the model predicted and therefore the model is validated. The actual result predicted for the maximum production was found to be nearly the same for the composition of Sucrose (3%); Yeast Extract
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(1%); Salts (0.2%); NaCl; (2%). The predicted response was 400 mg/L production of EPS whereas the actual response was 395±15 mg/L.
Batch Fermenter analysis Further, in order to determine the efficiency of the medium optimized by RSM in the production of EPS in a fermenter, batch fermentation was conducted. The culture was
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incubated at 37oC and pH 6.0. Samples were withdrawn every 3 h and production of EPS was seen to increase directly with time up to 21 h, following which it decreased. The maximum production of EPS was found to be 597 mg/L at 21st h (Fig. 6). The production of EPS was enhanced in fermenter when compared with the shake flask cultures.
DISCUSSION In this study, we report the isolation of an exopolysaccharide from a strain of probiotic organism, L. acidophilus, optimization of medium composition for maximum production of the EPS, and evaluation of the anti-cancer properties of EPS on the CaCo2 cell line.
EPS was found to induce cytotoxicity in CaCo2 cells. As the concentration of EPS increases the survival of the CaCo2 cells decreased. At 5 mg/ml significant reduction in the cell survival was observed. In earlier studies, various EPSs have been shown to exhibit anti-tumor properties. EPS from Lactobacillus casei,[21] Lactobacillus plantarum[22] and Lactobacillus acidophilus[23] have been shown to have anti-tumor properties against various cell lines. Since EPS extracted from L. acidophilus was found to exhibit anti-tumor properties, the mRNA expressions of two different genes were
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studied.
PPAR-γ is expressed abundant in adipose tissue, whereas expressions have been detected in colon, immune cells and retina. It plays a major role in fat metabolism and maturation of fat cells. Later, up-regulation of PPAR-γ has been showed to reduce the survival of
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colon cancer cells.[24]
Effect of EPS on the expression of two mRNAs was studied using RT-qPCR analysis. PPAR-γ is one of the nuclear hormonal receptor superfamily which plays a role in fat metabolism, inflammation and in apoptosis.[25] It is expressed in adipose tissue and plays a major role in the differentiation of adipocytes and also in insulin sensitivity. PPAR-γ is also one of the target for the ligands for the treatment of Type 2 diabetes mellitus.[26] There are various reports which demonstrate that up-regulation of PPAR-γ inhibits the growth of cancer cells.[27,28] Similar observation was made in the present study, where 5 mg/mL EPS treatment increased the expression of PPAR-γ under both the normoxic and hypoxic conditions. The effect of hypoxia on the down-regulation of the expression of PPAR-γ corroborates with the previous report where decreased expression of PPAR-γ is observed during hypoxia when compared to normoxia in kidney epithelial cells.[29] Although up-regulation of PPAR-γ was proposed to reduce the growth of colonic cancer cells and inhibit the anchorage of the of the cancer cells,[30] in one in vivo study where loss-function mutation of PPAR-γ is found to be associated with the development of colon cancer and the activation of PPAR-γ is reported to be protective or therapeutic [31] where as another in vivo experiment in mice showed the opposite results where growth of
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cancer cells was observed when PPAR-γ is activated.[30] PPAR-γ ligands were also shown to inhibit the growth of HT-29 cell line.[28] Therefore up-regulation in PPAR-γ might have resulted in the decreased cell viability under both treated conditions.
EPO is initially reported to play a major role in the erythropoiesis, whereas later studies revealed the angiogenic potential of EPO. EPO was reported to exhibit similar angiogenic
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potential as vascular endothelial growth factor, a potential angiogenic factor.[32] EPO has been reported to enhance the survival of the hypoxic tissue. Moreover it was also shown to increase the survival of the cancer cells under ischemic conditions.[33] EPO also play a major role in many cancers including colon cancer, where expression of EPO and EPO-R (Receptor of EPO) has been reported.[34] But, patients inflicted with colon cancer are often found to be anemic and they are supplemented with recombinant human EPO.[35] In the present study, EPS treatment was found to increase the expression EPO mRNA under normoxia, whereas no significant expression of EPO was detected in both control and treated samples under hypoxic conditions. Although EPO is a potent angiogenic factor and EPO-R is reported in cancer cell lines, addition of exogenous EPO was not found to affect the EPO-R mRNA in various colon carcinoma cell lines.[36] Therefore increase in EPO expression may not have a direct effect on the viability of cells. However, further studies are needed to ascertain the exact mechanism for the reduced expression of EPO under hypoxia.
PB design is very useful in determining the effect of various nutrient components in the production of a product in a fewer trials. Although quantitative analysis could not
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be performed, the significant factors affecting the production can be determined.[37] Statistical methods of medium optimization were performed to enhance the production of EPS. Medium optimization was performed by RSM and the characteristics of the medium were studied in the fermenter. Currently, RSM has been used to study the production of metabolites based on the dependent variables. This method not only provides the optimum values of the variables for maximum production but also gives the effects of
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interaction of various components during the fermentation. Normally, the step is usually preceded by the PB design in order to determine the factors that significantly influence the production. RSM is a study of the responses of interest with respect to several variables using mathematical and statistical techniques resulting in modeling and analysis for various applications.[38]
Lactobacillus sp generally result in low yields of EPS. The production of EPS is found to be around 26 mg/g of biomass in L. rhamnosus,[39] 730 mg/l by L. helveticus[40] and 800 mg/l by L. delbrukii subsp. Bulgaricus.[41] Yet, interest has been focused on this organism because it is categorized as GRAS (generally regarded as safe) and various textures have been produced.[5]
The medium components for CCRD were chosen by the PB design. As mentioned earlier the PB design yielded fructose, sucrose, yeast extract, Na2HPO4 and MgCl2 as significant factors. Since previous report has shown that sucrose is well suited for the growth of Lactobacilli and increases the production of EPS, sucrose was chosen as the carbon source.[42,43] Similarly, yeast extract also was found to have positive impact on the
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synthesis of EPS.[43] The screened components were then used for optimization of the medium by CCRD. The quadratic equation and the 3D plot obtained are highly useful in determining the interaction effect between variables and the corresponding change in the production of product.[44] When compared with the unoptimized media the synthesis of EPS was enhanced by a factor of 2.22 in optimized media. The efficacy of the optimized medium was checked in the fermenter under batch conditions. The production was found
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to be increased during batch fermentation which may be due to the controlled conditions provided in the fermenter.
CONCLUSION Media was optimized for the maximum production of EPS by L. acidophilus. The extracted EPS was found to inhibit the survival of the CaCo2 colon cancer cell line in a dose dependent manner under both normoxic and hypoxic conditions. qPCR studies demonstrated that EPS treatment up-regulated PPAR-γ expression (both normoxia and hypoxia) and EPO at normoxia. Further studies are needed to arrive at the exact mechanism that led to the changes in mRNA expression.
ACKNOWLEDGEMENT Author DV is grateful to CSIR, India for a Senior Research Fellowship.
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Sarraf, P.; Mueller, E.; Smith, W. M.; Wright, H. M.; Kum, J. B.; Aaltonen, L. A.; de la Chapelle, A.; Spiegelman, B.M.; Eng, C. Loss-of-function mutations in PPARγ associated with human colon cancer. Mol. Cell 1999, 3(6), 799-804. Jaquet, K.; Krause, K.; Tawakol-Khodai, M.; Geidel, S.; Kuck, K.H. Erythropoietin and VEGF exhibit equal angiogenic potential. Microvasc. Res. 2002, 64(2), 326-333. Lester, R. D.; Jo, M., Campana, W. M.; Gonias, S. L. Erythropoietin promotes MCF-7
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breast cancer cell migration by an ERK/mitogen-activated protein kinase-dependent pathway and is primarily responsible for the increase in migration observed in hypoxia. J. Biol. Chem. 2005, 280(47), 39273-39277. Batra, S.; Perelman, N.; Luck, L.R., Shimada, H.; Malik, P. Pediatric tumor cells express erythropoietin and a functional erythropoietin receptor that promotes angiogenesis and tumor cell survival. Lab. Invest. 2003, 83(10): 1477-1487. Kosmadakis, N.; Messaris, E.; Maris, A.; Katsaragakis, S.; Leandros, E.; Konstadoulakis, M. M.; Androulakis, G. Perioperative erythropoietin administration in patients with gastrointestinal tract cancer: prospective randomized double-blind study. Ann. Surg. 2003, 237(3), 417. Laugsch, M.; Metzen, E.; Svensson, T.; Depping, R.; Jelkmann, W. Lack of functional erythropoietin receptors of cancer cell lines. Int. J. Cancer 2008, 122(5), 1005-1011. Plackett, R. L.; Burman, J. P. The design of optimum multifactorial experiments. Biometrika, 1946, 305-325. Montgomery, D.C.; Runger, G.C. Applied Statistics and Probability for Engineers. John Wiley & Sons : NY, US, 2010.
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Gamar, L.; Blondeau, K.; Simonet, J.M. Physiological approach to extracellular polysaccharide production by Lactobacillus rhamnosus strain C83. J. Appl. Microbiol. 1997, 83(3), 281-287. Lin, T.Y.; Chien, M.F.C. Exopolysaccharides production as affected by lactic acid bacteria and fermentation time. Food Chem. 2007, 100(4), 1419-1423. Shene, C.; Bravo, S. Whey fermentation by Lactobacillus delbrueckii subsp. bulgaricus
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for exopolysaccharide production in continuous culture. Enzyme Microb. Tech. 2007, 40(6), 1578-1584. van Geel-Schutten, G.H.; Flesch, F.; Ten Brink, B.; Smith, M.R.; Dijkhuizen, L. Screening and characterization of Lactobacillus strains producing large amounts of exopolysaccharides. Appl. Microbiol. Biot. 1998, 50(6), 697-703. Liu, R. S.; Tang, Y. J. Tuber melanosporum fermentation medium optimization by Plackett–Burman design coupled with Draper–Lin small composite design and desirability function. Bioresource Technol. 2010, 101(9), 3139-3146. Wang, Z. W.; Liu, X. L. Medium optimization for antifungal active substances production from a newly isolated Paenibacillus sp. using response surface methodology. Bioresource Technol. 2008, 99(17), 8245-8251.
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Table 1: Coding levels of the variables selected for optimization Independent Symbols Coding Levels Variables
-α
-1
0
+1
+α
(%) Sucrose
A
1
2
3
4
5
Yeast
B
0.2
0.6
1.0
1.4
1.8
Salts
C
0.10
0.15
0.20
0.25
0.3
Sodium
D
0.5
1.25
2.0
2.75
3.5
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Extract
Chloride
26
Table 2: PB design actual and the yield of EPS in the corresponding experiments S
R
Fact
Fact
Fact
Fact
Fact
Fac
Fact
Fact Fac Fact
Fact
Respo
t
u
or 1
or 2
or 3
or 4
or 5
tor
or 7
or 8
tor
or
or 11
nse
d
n
Glu
Lact Fruc
Sucr Pept 6
Tryp
Mg
9
10
NaH
EPS
cose
ose
ose
Yea tone
SO4
Ca
K2H
2PO4
mg/10
Cl2
PO4
0.6
0.2
0.60
0.60
21
0
0
0.6
0.6
0.20
0.60
26
0
0
0.6
0.2
0.60
0.60
13
0
0
0.2
0.6
0.60
0.60
18
0
0
0.6
0.6
0.20
0.20
19
0
0
0.6
0.2
0.20
0.20
17
0
0
0.2
0.2
0.20
0.60
25
0
0
0.2
0.2
0.60
0.20
24
tose
one
st
0mL
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Ext ract 7
1
3.00
0.50 0.50
0.50 1.50
0.5
1.50
0 8
2
3.00
3.00 0.50
0.50 0.50
1.5
0.50
0 1
3
0.50
3.00 3.00
3.00 0.50
0 6
0.5
0.50
0 4
0.50
0.50 0.50
3.00 0.50
1.5
1.50
0 4
5
0.50
3.00 0.50
3.00 1.50
0.5
1.50
0 3
6
3.00
0.50 3.00
3.00 0.50
1.5
1.50
0 2
7
0.50
3.00 3.00
0.50 1.50
1.5
1.50
0 1
8
3.00
3.00 0.50
3.00 1.50
1.5
27
0.50
0 5
9
0.50
0.50 3.00
0.50 1.50
1.5
0.50
0 9
1
3.00
3.00 3.00
0.50 0.50
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0 1
1
1
1
1
1
2
2
0.5
1.50
0 3.00
0.50 3.00
3.00 1.50
0.5
0.50
0 0.50
0.50 0.50
0.50 0.50
0.5 0
28
0.50
0
0
0.6
0.6
0
0
0.2
0.6
0
0
0.2
0.6
0
0
0.2
0.2
0
0
0.60
0.20
21
0.60
0.20
19
0.20
0.60
17
0.20
0.20
27
Table 3: ANOVA for PB design Response 1
EPS
ANOVA for selected factorial model Analysis of variance table [Partial sum of squares – Type III] Source
Sum of
df
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squares
Mean
F value
Square
p-value Prob>F
Model
175.75
5
35.15
9.96
0.007
C-Fru
44.08
1
44.08
1.50
0.123
D-Suc
80.08
1
80.08
22.70
0.0031
F-YEX
18.75
1
18.75
5.31
0.0606
H-MgSO4
14.08
1
14.08
3.99
0.0927
K-K2HPO4 18.75
1
18.75
5.31
0.0606
Residual
21.17
6
3.53
Cor Total
196.92
11
29
Significant
Table 4: Design actual and EPS extracted in CCRD Std
Run
Factor 1
Factor 2
Factor 3
Factor 4
EPS
A: Sucrose B: Yeast
C: Salts
D: Sodium
production
(%)
(%)
Chloride
(mg/100ml)
Extract
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(%)
(%)
9
1
2.00
0.60
0.15
2.75
18
10
2
4.00
0.60
0.15
2.75
26
17
3
1.00
1.00
0.20
2.00
21
13
4
2.00
0.60
0.25
2.75
22
15
5
2.00
1.40
0.25
2.75
24
7
6
2.00
1.40
0.25
1.25
23
11
7
2.00
1.40
0.15
2.75
24
24
8
3.00
1.00
0.20
3.50
22
26
9
3.00
1.00
0.20
2.00
40
23
10
3.00
1.00
0.20
0.50
17
3
11
2.00
1.40
0.15
1.25
19
25
12
3.00
1.00
0.20
2.00
39
5
13
2.00
0.60
0.25
1.25
21
27
15
3.00
1.00
0.20
2.00
42
6
15
4.00
0.60
0.25
1.25
24
8
16
4.00
1.40
0.25
1.25
26
12
17
4000
1.40
0.15
2.75
29
20
18
3.00
1.80
0.20
2.00
33
30
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4
19
4.00
1.40
0.15
1.25
28
21
20
3.00
1.00
0.10
2.00
29
29
21
3.00
1.00
0.20
2.00
40
14
2
4.00
0.60
0.25
2.75
31
2
23
4.00
0.60
0.15
1.25
25
18
24
5.00
1.00
0.20
2.00
35
1
25
2.00
0.60
0.15
1.25
18
22
26
3.00
1.00
0.30
2.00
32
16
24
4.00
1.40
0.28
2.75
33
30
28
3.00
1.00
0.20
2.00
41
19
29
3.00
0.20
0.20
2.00
26
28
30
3.00
1.00
0.20
2.00
38
31
Table 5: ANOVA for CCRD ANOVA FOR RESPONSE SURFACE QUADRATIC MODEL Analysis of variance table [Partial sum of squares – type III] Source
Sum of
Df
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squares
Mean
F value
Square
p-value Prob>F
Model
1602.38
14
114.46
27.51
Preparative Biochemistry and Biotechnology Publication details, including instructions for authors and subscription information: http://www.tandfonline.com/loi/lpbb20
Optimization of Anticancer Exopolysaccharide Production From Probiotic Lactobacillus Acidophilus by Response Surface Methodology ab
a
b
Venkataraman Deepak , Sureshbabu Ram Kumar Pandian , Shiva. D. Sivasubramaniam , a
a
Hariharan Nellaiah & Krishnan Sundar a
Department of Biotechnology, Kalasalingam University, Krishnankoil, Tamilnadu, India
b
School of Science and Technology, Nottingham Trent University, Nottingham, UK Accepted author version posted online: 01 Apr 2015.
Click for updates To cite this article: Venkataraman Deepak, Sureshbabu Ram Kumar Pandian, Shiva. D. Sivasubramaniam, Hariharan Nellaiah & Krishnan Sundar (2015): Optimization of Anticancer Exopolysaccharide Production From Probiotic Lactobacillus Acidophilus by Response Surface Methodology, Preparative Biochemistry and Biotechnology, DOI: 10.1080/10826068.2015.1031386 To link to this article: http://dx.doi.org/10.1080/10826068.2015.1031386
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Optimization of Anticancer Exopolysaccharide Production from Probiotic Lactobacillus acidophilus by Response Surface Methodology Venkataraman Deepak 1,2, Sureshbabu Ram Kumar Pandian1, Shiva. D. Sivasubramaniam2, Hariharan Nellaiah1, Krishnan Sundar1, 1
Department of Biotechnology, Kalasalingam University, Krishnankoil, Tamilnadu, India 2
School of Science and Technology, Nottingham Trent University, Nottingham, UK
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Corresponding Author Dr. Krishnan Sundar, Department of Biotechnology, Kalasalingam University, Krishnankoil–626126, Tamilnadu, India. Email: [email protected]
Abstract Colorectal cancer (CRC) is one of the leading causes of cancer-related deaths in the Western world. Recently, much attention has been focused on decreasing the risk of CRC by consuming probiotics. In the present study exopolysaccharide (EPS) extracted from Lactobacillus acidophilus was found to inhibit the growth of CaCo2 colon cancer cell line in a dose dependent manner. The experiment was performed in both normoxic and hypoxic conditions and EPS was found to reduce the survival of CaCo2 cell line in both the conditions. qPCR studies demonstrated that EPS treatment up-regulated the expression of Peroxisome Proliferator Activator Receptor–γ (PPAR-γ) in both normoxia and hypoxia conditions, whereas it up-regulated the expression of erythropoietin (EPO) in normoxic condition but there was no significant expression under hypoxic conditions. Hence, the EPS production was optimized by Plackett Burnam design followed by central composite rotatory design. The optimized production of EPS at 24 h was found to be 400 mg/L. During batch cultivation the production peaked at 21st h resulting in an EPS concentration of 597 mg/l.
1
Key Words: Exopolysaccharides; Colon cancer; CaCo-2; PPAR- γ; EPO expression, response surface methodology
INTRODUCTION Lactic Acid Bacteria (LAB) have been a source of innumerable health benefits to the human population. Consumption of LAB with food or supplements was found to reduce
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the level of serum cholesterol,[1] and removal of pathogenic bacteria from the intestine,[2] though the main focus of LAB formulations is to balance the microbial population of the intestine.[3] The potential protective influence of LAB against colon cancer is also reported.[4]
Among various LAB, L. acidophilus is part of the intestinal microflora and one of the extensively used non-pathogenic strains for various health benefits.[2] Until recently, Lactobacillus acidophilus has been reported to prevent cancer by binding with the monoamines formed during cooking of meat; and by inactivation of enzymes that produce carcinogens (e.g. β-glucuronidase). EPS are polymers of sugars, which are nothing but long chained polysaccharides. Various LAB have been shown to synthesize EPS.[5] EPS have been shown to enhance taste in food substances,[5] confer immunomodulation with antioxidative effects,[6] and reduce the risk of colon cancer.[4] According to current statistics, colorectal cancer (CRC) has been the third most common type of cancer in men and second in women.[7] Although the incidence of colon cancer is less compared to rectal cancer in India, its numbers are constantly increasing.[8] Recent studies also show that people eating red meat are prone to CRC.[9] Hypoxia -
2
environments with low oxygen levels are often encountered in cancer, including colon cancer. The cancer cells multiply faster than the formation of vasculature and often results in hypoxic regions which is resistant to both radiotherapy and chemotherapy. Hypoxia, results in modifications in the expression pattern of various genes, resulting in the persistent proliferation of the cancer cells and also tumor vasculature.[10]
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This report mainly focuses on the determination of anti-proliferative activities of EPS extracted from L. acidophilus. The components were then optimized for maximum production by Plackett-Burman (PB) and Central Composite Rotatable Design (CCRD), followed by batch studies in a fermenter. Response surface methodology (RSM) involves regression analysis and can be used to predict the interaction of various factors involved in optimization, which is not possible with the conventional one-factor-at-a-time method. RSM has been previously used to optimize the production of various enzymes,[11, 12] biopolymers,[13] biomass, [14] oat milk production, [15] and even exopolysaccharides from Lactobacillus delbrukii.[16]
EXPERIMENTAL Culture Lactobacillus acidophilus (10307) was obtained from Microbial Type Culture Collection (MTCC), IMTECH, Chandigarh, India. The subculture was renewed every fortnight in MRS agar (Hi-Media, India), maintained at 4oC and used for experiments.
3
Characterization of EPS by FT-IR EPS was essentially produced in MRS medium (37°C, pH 6.5) and extracted by using cold-ethanol method. Initially, the culture was collected and TCA was added to the final concentration of 10%. The mixture was incubated at 4ºC for 3 h and the precipitate was centrifuged and discarded. To the supernatant ice-cold ethanol was added in an equal ratio and incubated at 4ºC overnight. EPS which is formed as a precipitate was collected.
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EPS was then purified by repeatedly dissolving it in distilled water and extraction with cold ethanol. The purified EPS was dialysed and used in further studies.[17] The EPS extracted was dried using a vacuum drier for 24 h and subjected to FT-IR using the KBr pellet method. The pellet was analyzed for FT-IR spectrum using a Fourier Transform IR Spectrometer (Shimadzu, Japan) in the range of 400-4500 cm-1.
Cell line and Treatment conditions CaCo2 cell line, kindly offered by Prof. Stephen Forsythe, Professor, Nottingham Trent University, UK, was maintained in EMEM supplemented with 10% serum. To determine the effect of EPS on CaCo2 cells under normoxic conditions, cells were seeded into a 96 well plate with 1.25 x 103 cells per well and incubated at 37oC in a humidified atmosphere containing 5% CO2. For treatment under hypoxic conditions (2% oxygen), cells were seeded into a 96 well plate with 3 x 103 cells per well and incubated at 37oC in an atmosphere containing 2% oxygen and 5% CO2. Later the cells were treated with various concentrations of EPS and the survival was checked after 48 hr using MTT assay. MTT was added to the media and incubated for 1 h. The formed formazon crystals were
4
dissolved using DMSO and the obtained A570 was compared with that of the control.
Real-Time Quantitative PCR studies Real-time quantitative PCR was used to determine the status of mRNAs of two factors PPARγ and EPO. After treating the CaCo2 cells with the toxic concentration of EPS, mRNA was extracted and converted to cDNA by the method prescribed by the
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manufacturer (Superscript™ II Reverse Transcriptase Kit). Obtained cDNA was either used for further studies or stored in 4oC for future use. qPCR reaction mixture with 5 µM of forward and reverse primers, 50 pg of cDNA template, AmpliTaq Gold polymerase and SYBR green PCR master mix (Biorad) was prepared and Real-time qPCR studies were performed. The primer sequences used were PPARγ (Annealing Temp. 54oC) forward 5’–GCTGTGCAGGAGATCACAGA–3’, Reverse 3’GGCTCCATAAAGTCACCAA-5’; EPO (Annealing Temp. 56.1oC) forward 5’GCCAGAGGAACTGTCCAGAG -3’, reverse 3’-CAGGTCATCCTGTCCCTGATP-5’. Each product was amplified for 40 cycles. For normalization of the cycle threshold (Ct) values for each cDNA template, Ct values of three control genes were used namely GAPDH (Glyceraldehyde 3-phosphate dehydrogenase), HGPRT-1 (hypoxanthine guanine phosphoribosyl transferase-1) and TBP-1 (Tat-binding protein-1, a component of 26S proteasome).[18]
Response Surface Methodology Choice of medium components using Plackett-Burman design
5
In order to select the significant components responsible for the production of EPS, various nutrients have been checked. The design consisted of 11 components (4 carbon sources, 3 nitrogen sources and 4 Salts) and 12 experiments were performed. The nutrients selected were Glucose, Lactose, Fructose, Sucrose, Peptone, Yeast Extract, Tryptone, MgSO4, CaCl2, K2HPO4 and NaH2PO4. The pH was maintained at 6.5 and temperature at 37oC. The experimental design, with coded values, is shown in Table 1.
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After 24 h, EPS was extracted and the response was analyzed. From the response the components that significantly affected the production of EPS were selected and used for CCRD.
Effect of pH on the production of EPS In order to determine the pH at which the production was optimum, the pH of the media was varied from 4 -9 at the interval of 0.5 and effect was determined.
Effect of time on production of EPS In order to determine the effect of time on the production of EPS, the bacterial culture was incubated for 36 h. The EPS was extracted every 6 h and the amount of EPS produced was determined.
Effect of Temperature on the production of EPS In order to assess the effect of temperature on the production of EPS, the bacterial culture was incubated at various temperatures ranging from 20°C – 50°C and production of EPS
6
was analyzed.
Effect of carbon source on the production of EPS In order to determine the concentration of carbon source at which the EPS production is enhanced the concentration of carbon source is varied from 1% to 5%.
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After 24 h, EPS produced was extracted and quantified.
Effect of nitrogen source on the production of EPS In order to determine the concentration of nitrogen source at which the EPS production is enhanced the concentration of nitrogen source is varied from 0.25% to1.5%. After 24 h, EPS produced was extracted and quantified.
Medium optimization by Central Composite Rotary Design After the variables for the production of EPS were screened, a Central Composite Rotatable Design was performed to optimize the media and to obtain a quadratic model for the production of EPS by L. acidophilus. The model consists of various trials with quadratic points and central points with the production of desired product (EPS production) as response. The design of experiments was generated using Design Expert software (Version 8.0 Trial, Stat-Ease, Inc., Minneapolis, USA). The design consists of 30 experiments with 6 trails for the central compositions replications, 8 axial trials and 16 trials for factorial design. The experiment consisted of four different variables A – Sucrose; B – Yeast Extract; C – A mixture of Salts (KH2PO4 & MgSO4 (1:1)); D – NaCl at 5 coded levels (-α, -1, 0, +1, +α) as shown in Table 2. The actual levels of the variables
7
for the CCRD design were determined by the PB design and the reference to the onefactor-at-a-time determination of media composition. The impact of each of the four variables on the production of product (EPS) is given by second-order polynomial equation given by
Y= B0 + B1 X1 + B2 X2 + B3 X3 + B4 X4 + B12 X1 X2 + B13 X1 X3 + B14 X1 X4 + B23 X2 X3
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+ B24 X2 X4 + B34 X3 X4 + B11 X12 + B22X22+B33X32+B44X42
Where X1, X2, X3, X4 are input variables which here corresponds to A – Sucrose; B – Yeast Extract; C – A mixture of Salts (KH2PO4 & MgSO4 (1:1)); D – NaCl respectively. The coefficients B corresponds to linear, cross-product and quadratic coefficients. The experiment was performed in a media volume of 100 ml at pH 6.0 and 37°C.
Fermenter Studies The efficacy of the CCRD-optimized medium to produce EPS was determined in batch fermentation using a 3L bench-top fermenter (Bioengineering, KLF 2000, Switzerland). Initially, the medium components were sterilized in situ and inoculated with 10% (v/v) of seed. The conditions maintained were 30°C, 200 rpm, pH 6.0 and aerated at the rate of 1.67 vvm for 24 h. Samples were withdrawn every 3 h and the EPS was extracted.
Statistical Methods Analysis was performed through Graphpad Prism 6 software. For MTT assay and RT qPCR studies, Student’s ‘t’ test was used for the analysis and **p F) < 0.00001) indicates that the model is highly significant. The fitness of the model was given by the R-squared value which is 0.96. This shows that the variation in the production of EPS is 96% attributed to the variables and only less than 4% could not be explained by the model. The predicted R-squared value of 0.8100 is in reasonable agreement with the “Adj R-Squared” vaue of 0.9275 which confirms the significance of the model.The statistically insignificant lack of fit value of ((Prob>F) = 2.62 shows that the model is adequate for the prediction of the EPS production in the range of the nutrients employed. Coeffecient of variation was found to be 7.23% which is low and makes the model precise and reliable. The significane of the values is given in Table 5. Higher the value of t-test and lower the p value shows that the coefficient terms are highly significant. The significant variables
13
from this design include A, B, C, D, A2, B2, C2 and D2. Therefore eliminating the insignificant terms
Y = 40.00 + 3.38 * A+ 1.46 * B + 0.96 * C +1.37 * D - 3.41 * A2 +3.03 * B2- 2.78 * C2- 5.53 * D2 (Eq. 2) ‘‘Adeq Precision” measures the signal (response)-to-noise (deviation) ratio, a
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ratio greater than 4 being desirable. In the present study involving medium optimization for EPS production, the ratio of 9.265 indicated an adequate signal.
The 3D-graphs obtained are shown in Figure 5. The 3D plot obtained is the graphical representation of the obtained regression equation. The graphs are drawn based on the effect of two variables on the EPS production by keeping the other two variables as zero. Fig. 5A, 5B, 5C, 5D, 5E and 5F show the interaction of Sucrose vs Yeast extract; Sucrose vs salts; Sucrose vs NaCl; Yeast extract vs salts; Yeast extract with NaCl; Salts vs NaCl respectively. The final optimized concentration of EPS from CCRD was 400 mg/L.
Validation of the model The production of exopolysaccharides was validated using the model proposed. The results obtained from the experiment were similar to the model predicted and therefore the model is validated. The actual result predicted for the maximum production was found to be nearly the same for the composition of Sucrose (3%); Yeast Extract
14
(1%); Salts (0.2%); NaCl; (2%). The predicted response was 400 mg/L production of EPS whereas the actual response was 395±15 mg/L.
Batch Fermenter analysis Further, in order to determine the efficiency of the medium optimized by RSM in the production of EPS in a fermenter, batch fermentation was conducted. The culture was
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incubated at 37oC and pH 6.0. Samples were withdrawn every 3 h and production of EPS was seen to increase directly with time up to 21 h, following which it decreased. The maximum production of EPS was found to be 597 mg/L at 21st h (Fig. 6). The production of EPS was enhanced in fermenter when compared with the shake flask cultures.
DISCUSSION In this study, we report the isolation of an exopolysaccharide from a strain of probiotic organism, L. acidophilus, optimization of medium composition for maximum production of the EPS, and evaluation of the anti-cancer properties of EPS on the CaCo2 cell line.
EPS was found to induce cytotoxicity in CaCo2 cells. As the concentration of EPS increases the survival of the CaCo2 cells decreased. At 5 mg/ml significant reduction in the cell survival was observed. In earlier studies, various EPSs have been shown to exhibit anti-tumor properties. EPS from Lactobacillus casei,[21] Lactobacillus plantarum[22] and Lactobacillus acidophilus[23] have been shown to have anti-tumor properties against various cell lines. Since EPS extracted from L. acidophilus was found to exhibit anti-tumor properties, the mRNA expressions of two different genes were
15
studied.
PPAR-γ is expressed abundant in adipose tissue, whereas expressions have been detected in colon, immune cells and retina. It plays a major role in fat metabolism and maturation of fat cells. Later, up-regulation of PPAR-γ has been showed to reduce the survival of
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colon cancer cells.[24]
Effect of EPS on the expression of two mRNAs was studied using RT-qPCR analysis. PPAR-γ is one of the nuclear hormonal receptor superfamily which plays a role in fat metabolism, inflammation and in apoptosis.[25] It is expressed in adipose tissue and plays a major role in the differentiation of adipocytes and also in insulin sensitivity. PPAR-γ is also one of the target for the ligands for the treatment of Type 2 diabetes mellitus.[26] There are various reports which demonstrate that up-regulation of PPAR-γ inhibits the growth of cancer cells.[27,28] Similar observation was made in the present study, where 5 mg/mL EPS treatment increased the expression of PPAR-γ under both the normoxic and hypoxic conditions. The effect of hypoxia on the down-regulation of the expression of PPAR-γ corroborates with the previous report where decreased expression of PPAR-γ is observed during hypoxia when compared to normoxia in kidney epithelial cells.[29] Although up-regulation of PPAR-γ was proposed to reduce the growth of colonic cancer cells and inhibit the anchorage of the of the cancer cells,[30] in one in vivo study where loss-function mutation of PPAR-γ is found to be associated with the development of colon cancer and the activation of PPAR-γ is reported to be protective or therapeutic [31] where as another in vivo experiment in mice showed the opposite results where growth of
16
cancer cells was observed when PPAR-γ is activated.[30] PPAR-γ ligands were also shown to inhibit the growth of HT-29 cell line.[28] Therefore up-regulation in PPAR-γ might have resulted in the decreased cell viability under both treated conditions.
EPO is initially reported to play a major role in the erythropoiesis, whereas later studies revealed the angiogenic potential of EPO. EPO was reported to exhibit similar angiogenic
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potential as vascular endothelial growth factor, a potential angiogenic factor.[32] EPO has been reported to enhance the survival of the hypoxic tissue. Moreover it was also shown to increase the survival of the cancer cells under ischemic conditions.[33] EPO also play a major role in many cancers including colon cancer, where expression of EPO and EPO-R (Receptor of EPO) has been reported.[34] But, patients inflicted with colon cancer are often found to be anemic and they are supplemented with recombinant human EPO.[35] In the present study, EPS treatment was found to increase the expression EPO mRNA under normoxia, whereas no significant expression of EPO was detected in both control and treated samples under hypoxic conditions. Although EPO is a potent angiogenic factor and EPO-R is reported in cancer cell lines, addition of exogenous EPO was not found to affect the EPO-R mRNA in various colon carcinoma cell lines.[36] Therefore increase in EPO expression may not have a direct effect on the viability of cells. However, further studies are needed to ascertain the exact mechanism for the reduced expression of EPO under hypoxia.
PB design is very useful in determining the effect of various nutrient components in the production of a product in a fewer trials. Although quantitative analysis could not
17
be performed, the significant factors affecting the production can be determined.[37] Statistical methods of medium optimization were performed to enhance the production of EPS. Medium optimization was performed by RSM and the characteristics of the medium were studied in the fermenter. Currently, RSM has been used to study the production of metabolites based on the dependent variables. This method not only provides the optimum values of the variables for maximum production but also gives the effects of
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interaction of various components during the fermentation. Normally, the step is usually preceded by the PB design in order to determine the factors that significantly influence the production. RSM is a study of the responses of interest with respect to several variables using mathematical and statistical techniques resulting in modeling and analysis for various applications.[38]
Lactobacillus sp generally result in low yields of EPS. The production of EPS is found to be around 26 mg/g of biomass in L. rhamnosus,[39] 730 mg/l by L. helveticus[40] and 800 mg/l by L. delbrukii subsp. Bulgaricus.[41] Yet, interest has been focused on this organism because it is categorized as GRAS (generally regarded as safe) and various textures have been produced.[5]
The medium components for CCRD were chosen by the PB design. As mentioned earlier the PB design yielded fructose, sucrose, yeast extract, Na2HPO4 and MgCl2 as significant factors. Since previous report has shown that sucrose is well suited for the growth of Lactobacilli and increases the production of EPS, sucrose was chosen as the carbon source.[42,43] Similarly, yeast extract also was found to have positive impact on the
18
synthesis of EPS.[43] The screened components were then used for optimization of the medium by CCRD. The quadratic equation and the 3D plot obtained are highly useful in determining the interaction effect between variables and the corresponding change in the production of product.[44] When compared with the unoptimized media the synthesis of EPS was enhanced by a factor of 2.22 in optimized media. The efficacy of the optimized medium was checked in the fermenter under batch conditions. The production was found
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to be increased during batch fermentation which may be due to the controlled conditions provided in the fermenter.
CONCLUSION Media was optimized for the maximum production of EPS by L. acidophilus. The extracted EPS was found to inhibit the survival of the CaCo2 colon cancer cell line in a dose dependent manner under both normoxic and hypoxic conditions. qPCR studies demonstrated that EPS treatment up-regulated PPAR-γ expression (both normoxia and hypoxia) and EPO at normoxia. Further studies are needed to arrive at the exact mechanism that led to the changes in mRNA expression.
ACKNOWLEDGEMENT Author DV is grateful to CSIR, India for a Senior Research Fellowship.
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Table 1: Coding levels of the variables selected for optimization Independent Symbols Coding Levels Variables
-α
-1
0
+1
+α
(%) Sucrose
A
1
2
3
4
5
Yeast
B
0.2
0.6
1.0
1.4
1.8
Salts
C
0.10
0.15
0.20
0.25
0.3
Sodium
D
0.5
1.25
2.0
2.75
3.5
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Extract
Chloride
26
Table 2: PB design actual and the yield of EPS in the corresponding experiments S
R
Fact
Fact
Fact
Fact
Fact
Fac
Fact
Fact Fac Fact
Fact
Respo
t
u
or 1
or 2
or 3
or 4
or 5
tor
or 7
or 8
tor
or
or 11
nse
d
n
Glu
Lact Fruc
Sucr Pept 6
Tryp
Mg
9
10
NaH
EPS
cose
ose
ose
Yea tone
SO4
Ca
K2H
2PO4
mg/10
Cl2
PO4
0.6
0.2
0.60
0.60
21
0
0
0.6
0.6
0.20
0.60
26
0
0
0.6
0.2
0.60
0.60
13
0
0
0.2
0.6
0.60
0.60
18
0
0
0.6
0.6
0.20
0.20
19
0
0
0.6
0.2
0.20
0.20
17
0
0
0.2
0.2
0.20
0.60
25
0
0
0.2
0.2
0.60
0.20
24
tose
one
st
0mL
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Ext ract 7
1
3.00
0.50 0.50
0.50 1.50
0.5
1.50
0 8
2
3.00
3.00 0.50
0.50 0.50
1.5
0.50
0 1
3
0.50
3.00 3.00
3.00 0.50
0 6
0.5
0.50
0 4
0.50
0.50 0.50
3.00 0.50
1.5
1.50
0 4
5
0.50
3.00 0.50
3.00 1.50
0.5
1.50
0 3
6
3.00
0.50 3.00
3.00 0.50
1.5
1.50
0 2
7
0.50
3.00 3.00
0.50 1.50
1.5
1.50
0 1
8
3.00
3.00 0.50
3.00 1.50
1.5
27
0.50
0 5
9
0.50
0.50 3.00
0.50 1.50
1.5
0.50
0 9
1
3.00
3.00 3.00
0.50 0.50
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0 1
1
1
1
1
1
2
2
0.5
1.50
0 3.00
0.50 3.00
3.00 1.50
0.5
0.50
0 0.50
0.50 0.50
0.50 0.50
0.5 0
28
0.50
0
0
0.6
0.6
0
0
0.2
0.6
0
0
0.2
0.6
0
0
0.2
0.2
0
0
0.60
0.20
21
0.60
0.20
19
0.20
0.60
17
0.20
0.20
27
Table 3: ANOVA for PB design Response 1
EPS
ANOVA for selected factorial model Analysis of variance table [Partial sum of squares – Type III] Source
Sum of
df
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squares
Mean
F value
Square
p-value Prob>F
Model
175.75
5
35.15
9.96
0.007
C-Fru
44.08
1
44.08
1.50
0.123
D-Suc
80.08
1
80.08
22.70
0.0031
F-YEX
18.75
1
18.75
5.31
0.0606
H-MgSO4
14.08
1
14.08
3.99
0.0927
K-K2HPO4 18.75
1
18.75
5.31
0.0606
Residual
21.17
6
3.53
Cor Total
196.92
11
29
Significant
Table 4: Design actual and EPS extracted in CCRD Std
Run
Factor 1
Factor 2
Factor 3
Factor 4
EPS
A: Sucrose B: Yeast
C: Salts
D: Sodium
production
(%)
(%)
Chloride
(mg/100ml)
Extract
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(%)
(%)
9
1
2.00
0.60
0.15
2.75
18
10
2
4.00
0.60
0.15
2.75
26
17
3
1.00
1.00
0.20
2.00
21
13
4
2.00
0.60
0.25
2.75
22
15
5
2.00
1.40
0.25
2.75
24
7
6
2.00
1.40
0.25
1.25
23
11
7
2.00
1.40
0.15
2.75
24
24
8
3.00
1.00
0.20
3.50
22
26
9
3.00
1.00
0.20
2.00
40
23
10
3.00
1.00
0.20
0.50
17
3
11
2.00
1.40
0.15
1.25
19
25
12
3.00
1.00
0.20
2.00
39
5
13
2.00
0.60
0.25
1.25
21
27
15
3.00
1.00
0.20
2.00
42
6
15
4.00
0.60
0.25
1.25
24
8
16
4.00
1.40
0.25
1.25
26
12
17
4000
1.40
0.15
2.75
29
20
18
3.00
1.80
0.20
2.00
33
30
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4
19
4.00
1.40
0.15
1.25
28
21
20
3.00
1.00
0.10
2.00
29
29
21
3.00
1.00
0.20
2.00
40
14
2
4.00
0.60
0.25
2.75
31
2
23
4.00
0.60
0.15
1.25
25
18
24
5.00
1.00
0.20
2.00
35
1
25
2.00
0.60
0.15
1.25
18
22
26
3.00
1.00
0.30
2.00
32
16
24
4.00
1.40
0.28
2.75
33
30
28
3.00
1.00
0.20
2.00
41
19
29
3.00
0.20
0.20
2.00
26
28
30
3.00
1.00
0.20
2.00
38
31
Table 5: ANOVA for CCRD ANOVA FOR RESPONSE SURFACE QUADRATIC MODEL Analysis of variance table [Partial sum of squares – type III] Source
Sum of
Df
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squares
Mean
F value
Square
p-value Prob>F
Model
1602.38
14
114.46
27.51
