SEARCH

SEARCH BY CITATION

Keywords:

  • cholesterol;
  • hypercholesterolemia;
  • lactic acid bacteria;
  • response surface methodology

Abstract

  1. Top of page
  2. Abstract
  3. MATERIALS AND METHODS
  4. RESULTS
  5. DISCUSSION
  6. DISCLOSURE
  7. ACKNOWLEDGMENTS
  8. REFERENCES

Lactobacillus casei LA-1 isolated from a nondairy fermented source was evaluated for its in vitro ability to reduce cholesterol. The bacterium tested positive for bile salt deconjugation in relation to cholesterol removal. Tested growth-associated physiological variables such as pH, temperature and inoculum size were all found to have significant effects on in vitro cholesterol reduction and biomass production (both P < 0.005). Furthermore, a central composite design was used to evaluate the effects of significant variables and their interactions. A linear regression model was developed for in vitro cholesterol reduction as a function of growth-associated variables. Maximum cholesterol reduction achieved was 45% whereas maximum biomass yield of 2.34 optical density was observed at the central point. Our study possibly indicates that the growth of L. casei LA-1 depends on its cholesterol removing ability.

List of Abbreviations
BLAST

Basic Local Alignment Search Tool

BSH

bile salt hydrolase

CCD

central composite design

CFU

colony-forming units

KOH

potassium hydroxide

L. casei

Lactobacillus casei

MRS

deMan Rogosa Sharpe

OD

optical density

OFAT

one-factor-at-a-time-method

rDNA

ribosomal deoxyribo nucleic acid

RSM

response surface method

Hypercholesterolemia is the most important risk factor for cardiovascular diseases and is considered one of the major causes of death and disability in many countries. Previous studies have shown that a 1% reduction in serum cholesterol concentration may reduce the risk of coronary heart disease by 2–3% [1]. Drug therapy for hypercholesterolemia has undesirable side effects that have raised concerns about their therapeutic use. Hence, a more natural method of decreasing serum cholesterol concentration in humans is required.

Lactobacilli and other lactic acid-producing bacteria play important roles in balancing digestive functions and helping with cholesterol removal, although research has not yet established a dose-effect relationship. Attempts to understand the influence on human health of live microorganisms, especially lactic acid bacteria, in foods have a very long history. Elie Metchnikoff proposed that the longevity of Bulgarians is in part due to their consumption of large quantities of fermented milk containing lactobacilli [2]. Because of their ability to deconjugate bile salts, in recent years there has been interest in the possibility of using lactic acid bacteria as biological hypocholesterolemic agents [3, 4]. Several studies have proposed a relationship between consumption of lactic acid bacteria and reduction of cholesterol concentrations in blood of humans [5] rats [3, 4] and chickens [6, 7] and in egg yolk [8]. The presence of BSH has a selective advantage for this bacterium in bile salt rich environments [9]. BSH activity benefits the bacterium by enhancing its resistance to conjugated bile salts and increasing its survival in the gastrointestinal tract and thus its ability to colonize it [10, 11]. Studies on deconjugation of bile salts and cholesterol-reducing ability of lactobacilli have mostly been carried out on strains isolated from humans [12], swine [13] and fermented milk preparations [9, 13]; there is very little information on lactobacilli strains from nondairy fermented products. However, non-dairy probiotic products have considerable worldwide importance because of the ongoing trend toward vegetarianism, allergenic milk proteins, milk cholesterol content and the high prevalence of lactose intolerance in many populations around the world. Previous studies have reported the ability of Lactobacillus acidophilus [14, 15] and bifidobacteria [16] to assimilate cholesterol from laboratory media. Thus, both types of bacteria may have the potential to reduce serum cholesterol in humans. Many attempts have been made to elucidate the mechanism(s) involved in the hypocholesterolemic action of lactic acid bacterial strains. One proposed mechanism is reduction of cholesterol by the cell wall during growth [17, 18]. Another possible mechanism is deconjugation of bile salts by bacteria producing BSH. Thus, the concept of actively managing colonic microflora with the aim of reducing serum cholesterol is of great importance.

Response surface methodology is a statistical and mathematical method that involves utilizing main and interaction effects to account for curvature, improve optimal process settings and troubleshoot process problems and weak points [19]. Researchers have successfully utilized it to optimize compositions of microbiological media, conditions of enzyme hydrolysis and parameters for food preservation and fermentation processes [20]. Previous studies have used conventional methods (such as assessing one factor at a time) to evaluate the in vitro performance of probiotics along with several other factors in the removal of cholesterol. These methods, however, are time consuming and require a large number of experiments to clarify the effects of individual factors. Besides, there is no established statistical method that distinguishes interaction effects from the main effects. Furthermore, up to now, there are no published studies on the use of RSM for optimization and modeling of in vitro cholesterol reduction as a function of growth-associated factors. Thus, the goal of this study was to study the ability of previously isolated probiotic Lactobacillus casei LA-1 to remove cholesterol in vitro and to model cholesterol reduction as a function of growth-associated physiological variables.

MATERIALS AND METHODS

  1. Top of page
  2. Abstract
  3. MATERIALS AND METHODS
  4. RESULTS
  5. DISCUSSION
  6. DISCLOSURE
  7. ACKNOWLEDGMENTS
  8. REFERENCES

Bacterial strains and growth conditions

A probiotic strain, L. casei LA-1, was isolated from a mango pickle and selected as a probiotic in previous studies [21]. The strain was identified by sequencing of 16S rDNA gene followed by BLAST homology search. The nucleotide sequences were deposited with the National Center for Biotechnology Information database under GenBank Accession No. JN620211.

A freeze-dried culture of L. casei LA-1 was rehydrated for 10 min at room temperature in a medium containing 1.5% peptone, 1.0% tryptone, and 0.5% yeast extract (Himedia, Mumbai, India). Rehydrated culture (1% v/v) was transferred into MRS broth (Himedia) and incubated at 37°C for 24 hr under anaerobic conditions. The strain was maintained on MRS agar (Himedia) at 4°C.

Deconjugation of bile salts

Bile salt hydrolase activity was detected using a previously described procedure [22]. Briefly, 10 µL of overnight cultures were spotted onto MRS agar plates supplemented with 0.5% (w/v) taurodeoxycholic acid sodium salt and 0.37 g/L of calcium chloride. The plates were incubated anaerobically for 72 hr. The strains with a white precipitation zone surrounding the colony were considered as positive. L. acidophilus ATCC 43121 and Enterococcus faecium E 179 were used as BSH-positive and BSH-negative control strains, respectively.

In vitro cholesterol reduction

Water-soluble cholesterol (5 mg/mL in 50% ethanol) was filter sterilized and added to MRS broth supplemented with 0.3% ox bile at a final concentration of 70 µg/mL. The MRS broth was inoculated with test culture L. casei LA-1 (107 CFU/mL) and incubated anaerobically at 37°C for 24 hr. After incubation, cells were centrifuged (10,000 g at 48°C for 10 min), and the remaining cholesterol concentration in the broth determined using a colorimetric method as described earlier [23]. Then 1 mL of the aliquot was added to 1 mL of KOH (33%, w/v) and 2 mL of absolute ethanol, vortexed for 1 min and left at 37°C for 15 min. After cooling, 2 mL of distilled water and 3 mL of hexane were added followed by vortexing for 1 min. Then 1 mL of the hexane layer was transferred into a glass tube and evaporated. The residue was immediately dissolved in 2 mL of o-phthalaldehyde reagent. After complete mixing, 0.5 mL of concentrated H2SO4 was added, and the mixture again vortexed for 1 min. Finally, the absorbance was read at 550 nm after 10 min.

Similar experiments for in vitro reduction of cholesterol were performed with dead biomass: the cells were heat sterilized (by autoclaving at 121°C/5 min) and the amount of cholesterol thus removed from broth determined by subtracting the amount in each broth sample (mg/mL) from the amount present in the un-inoculated (control).

Effect of varying growth-associated variables on cholesterol removal and biomass production by Lactobacillus casei LA-1

Different physiological variables, such as initial medium pH, temperature and inoculum size, were varied to analyze their effects on growth of L. casei and consequently of its ability to remove cholesterol. In a control experiment, a series of 100 mL flasks of MRS broth containing water-soluble cholesterol (70 µg/mL) were prepared as described above. After different incubation times, the cultures were examined for bacterial growth (OD 600nm), changes in culture pH, and cholesterol reduction.

To study the effect of temperature on bacterial growth and cholesterol reduction, another set of flasks were incubated for 24 hr at temperatures of 20–40°C and bacterial growth and cholesterol reduction in the culture medium observed. The effect of initial pH of the medium on bacterial growth and cholesterol reduction was determined by adjusting the MRS broth to different initial pH levels of 3.0, 5.0, 7.0 and 9.0 at an incubation temperature of 37°C for 24 hr, without agitation.

Variations in inoculum size over the range 0.5–2.5 OD were incubated at 37°C for 24 hr without agitation. Bacterial growth and cholesterol reduction were determined at 4 hr intervals, as described above. The test variables that affect growth and cholesterol reduction were first studied by OFAT as described above to determine their effects and ranges individually. Then, an RSM using a batch culture system was applied to model changes in cholesterol concentrations in relation to bacterial growth as a function of growth-associated physiological variables to determine how to maximize in vitro reduction of cholesterol in the medium by the probiotic L. casei LA-1.

Optimizing in vitro cholesterol reduction and growth of Lactobacillus casei LA-1

Response surface optimization is a collection of statistical techniques for designing experiments, building models, evaluating the effects of various factors and searching for optimal conditions of various factors to produce the desired responses. Within the RSM, a CCD was employed to illustrate the nature of response surface in the experimental design and elucidate the optimal settings for the most significant independent variables as screened by the OFAT method. The total number of experimental combinations is 2k + 2k + n0, where K is the number of independent variables and n0 is the rotatable central point number. A total of 20 experiments were performed with variations in three independent factors, namely, pH, temperature, and inoculum size.

To develop a regression equation, these factors were coded according to the equation:

  • display math(1)

where XI is the coded value of the ith independent variable, xi is the natural value of the ith independent variable; xoi is the natural value of the ith independent variable at the centre point and is the difference in effect.

Once cholesterol reduction and growth of L. casei LA-1 had been determined for each trial, a second-order polynomial was fitted to the response data obtained from the design. The general polynomial equation is as follows:

  • display math(2)

where Y and Z are the predicted amount of cholesterol reduction and growth, β0 the model constant, βi the linear coefficient, βii the quadratic coefficient, βij the coefficient for the interaction effect and Xi a dimensionless coded value of xi (independent variable). The behavior of the system is explained by this quadratic equation.

Data were analyzed by a CCD experimental plan using the statistical software package Design-Expert (Version 8.0.1, Stat-Ease, Minneapolis, MN, USA). The fit quality of the model was evaluated by R2 and ANOVA. Statistical testing of the model was done by Fisher's statistical test. The robustness of the model and optimal values of variables were assessed by the determination coefficient, correlation coefficient (R) or F-test [24].

RESULTS

  1. Top of page
  2. Abstract
  3. MATERIALS AND METHODS
  4. RESULTS
  5. DISCUSSION
  6. DISCLOSURE
  7. ACKNOWLEDGMENTS
  8. REFERENCES

Deconjugation of bile salt hydrolase

L. casei LA-1 possesses BSH activity. In connection with this, it was noted in our previous study that it also has strong resistance to duodenal juice containing 0.5% bile salts [21], which is possibly relevant to its BSH activity [25]. Deconjugation of bile salts by BSH-positive bacteria leads to an increased demand for cholesterol which in turn prompts de novo synthesis of bile salts in the liver, thus possibly leading to reduction in serum cholesterol.

Biomass production of Lactobacillus casei LA-1 and in vitro cholesterol reduction in growth medium

The results of a control experiment in which cholesterol assimilation and biomass production by L. casei LA-1 during growth was assessed are shown in Figure 1. The cell density of L. casei LA-1 increased from 0.1 to 2.25 (OD600nm) during 24 hr of growth at 37°C. The maximum residual cholesterol in the culture medium was about 40%. The pH of the medium decreased from 7.0 to 3.5 over the same period. L. casei LA-1 produced good cholesterol reduction in the presence of bile salts. However, we also found that these strains did not remove any cholesterol in the absence of bile salts (data not shown). Assessment of the influence of heat-sterilized biomass on the uptake of cholesterol in MRS broth confirmed that resting cells are unable to remove cholesterol.

image

Figure 1. Cholesterol assimilation and biomass production during growth of Lactobacillus casei in deMan Rogosa Sharpe broth at 37°C. Residual cholesterol was also assayed and expressed as %.

Download figure to PowerPoint

Effect of growth-associated variables on in vitro cholesterol reduction and biomass production

The effect of incubation temperature on in vitro cholesterol was studied by incubating the producer strain at 25, 30, 35, and 40°C. Both maximum biomass production and maximum cholesterol reduction occurred at a temperature of 35°C. Furthermore, increasing temperature had a negative effect on cholesterol reduction and biomass production.

When different initial pH values in MRS broth in the range described above were assayed, it was found that a neutral pH is best for cholesterol reduction and that biomass production was maximal after an incubation of 24 hr.

When inoculum size was varied, it was found that inoculum size of 2.0 OD resulted in maximum cholesterol reduction and biomass production. Under the previously described conditions, further increases in inoculum size did not result in any increase in biomass production and cholesterol reduction. Dunn's multiple comparison test showed that all the above factors are significant (P < 0.05). These values suggest that all the tested factors have direct effects on cholesterol reduction and biomass production.

Response surface optimization of in vitro cholesterol reduction and biomass production by Lactobacillus casei LA-1

Response surface optimization was used to clarify both individual and combined effects of the above-mentioned variables in optimization of in vitro cholesterol reduction and biomass production by L. casei LA-1. In general, maximum cholesterol reduction was observed during the exponential growth phase and maximum biomass production when the cultures attained the stationary phase. Analysis of the screened data from a five-level response surface design was complex but led to identification of the key variables affecting cholesterol reduction and biomass production. Thus, a response surface design the CCD of which is a function of temperature, inoculum size and pH was centered in the region where high cholesterol reduction and biomass production were expected.

The results of the lab experiments were fed into Design-Expert software and analyzed using ANOVA when appropriate to the experimental design used. The ranges and coded and actual values of the selected variables are presented in Table 1. Based on the CCD, the experimental amounts of in vitro cholesterol removal and biomass production were determined and compared with the corresponding predicted amounts (Table 2). ANOVA and Fischer's F-test showed F-values of 8.58 and 14.04 for cholesterol removal and biomass production, respectively, which are greater than the tabulated values, thereby demonstrating the significance of the regression model. The regression equation obtained produced R2 value of 0.92 and 0.88 for cholesterol removal and biomass production, respectively (Table 3a and b). The closeness of the R2 value to 1.0 reflects the strength of the model. This statistical analysis also allowed determination of the contribution of experimental factors (signals) in comparison to noise (signal should be fairly large in comparison to noise). Thus, the estimated adequate precision of 8.91 and 10.72 for in vitro cholesterol removal and biomass production, respectively, representing the signal to noise ratio, is an adequate signal. The application of RSM yielded the following regression equations, which establish an empirical relationship between biomass production (Y); cholesterol removal (Z) and the test variables in actual units:

  • display math(3)
  • display math(4)
Table 1. Range of values for response surface method
 Independent variablesCoded levels
−α−101
ATemperature (°C)26.593035.04043.41
BpH3.9856.589.02
CInoculum size (OD)0.6611.522.34
Table 2. Coded experimental design and results for the response surface as a function of pH, temperature and inoculum size
RunsCoded valuesBiomass (OD)Cholesterol removal (%)Biomass (OD)Cholesterol removal (%)
Std.RunABCExperimentalPredicted
11930511.35291.1029
2540511.4251.1725
3330811.3251.1925
41740811.2241.0624
5430521.65321.5732
61540521.729.51.5929.5
7230821.8291.8229
8840821.6281.6428
9926.596.51.51.1211.2321
102043.406.51.51201.1420
1118353.971.50.9151.1815
121359.021.51.3301.3030
1316356.50.651.1371.4237
1410356.52.342.34452.3045
156356.51.52421.9942
1611356.51.52421.9942
1714356.51.52421.9942
1813356.51.51.99421.9942
1912356.51.52.02431.9943
207356.51.52411.9941
Table 3. Precision value of the model for biomass and cholesterol assimilation
Std. Dev.0.19R20.88
  1. Adeq, adequate; Adj., adjusted; CV, coefficient of variation; Pred., predicted; Std., standard.

Mean1.58Adj. R20.78
CV %12.33Pred. R20.13
PRESS2.90Adeq precision8.91
Std. Dev.3.33R20.92
Mean32.07Adj. R20.86
C.V. %10.40Pred. R20.46
PRESS834.79Adeq precision10.72

The significance of each co-efficient was determined by Fischer's F-test (Tables 4 and 5). The smaller the P-value and larger the F-value, the more significant is the corresponding co-efficient. Fischer's F-test showed that all the linear coefficients are significant (P < 0.05). These values suggest that these factors have direct effects on cholesterol removal and biomass production. The interaction terms were not statistically significant. The sign and magnitude of coefficients indicates the effects of the variables on the responses. Contour plots based on the interactions between the variables showed an increase in cholesterol removal and biomass production at the upper axis. An increase in biomass yield with increase in inoculum size versus temperature (Fig. 2a) was observed, whereas maximum cholesterol removal was obtained at the central point (Fig. 2b). Plotting of the normal values versus residuals showed that data were very close to the straight line and situated on both sides of it, indicating that model developed was fairly good (data not shown).

Table 4. ANOVA for response surface quadratic model of cholesterol removal
SourceSum of squaresdfMean squareF valueProbability > F 
Model1444.69160.5214.400.0001Significant
A-temperature7.5917.590.680.42 
B-pH18.11118.111.620.23 
C-inoculum size61.38161.385.500.04 
AB2.5312.530.220.64 
AC0.2810.280.0250.87 
BC0.0310.030.0020.95 
A2808.01808.0772.50<0.0001 
B2662.661662.6659.45<0.0001 
C20.8310.830.0740.79 
Residual111.451011.14   
Lack of fit109.45521.8954.720.0002 
Table 5. ANOVA for response surface quadratic model of bacterial growth of Lactobacillus casei LA-1
SourceSum of squaresdfMean squareF valueProbability > F 
Model2.9890.338.620.001Significant
A-temperature0.00910.0090.250.62 
B-pH0.0110.010.420.52 
C-inoculum size0.9410.9424.520.0006 
AB0.0210.020.520.48 
AC0.00110.0010.0320.86 
BC0.0110.010.290.60 
A21.1511.1530.170.0003 
B21.0111.0126.520.0004 
C20.0310.030.810.38 
Residual0.38100.03   
Lack of fit0.3850.071095.82< 0.0001 
image

Figure 2. Two-dimensional contour plots showing the effect of test variables on (a) biomass production (cell density) and (b) cholesterol removal.

Download figure to PowerPoint

Validation of the model equation

In order to determine the accuracy of the model, responses were numerically optimized using Design-Expert software. The criteria used for optimization and the predicted and actual (observed) response values are presented in Table 6. The main aim of the present study was to optimize the maximum amount of biomass production and cholesterol reduction, while keeping all the factors' values “in optimal range.” Using the given criteria, solutions having a desirability of 100% were selected and appropriate experiments conducted. The values of observed response for biomass (2.25 OD) and cholesterol reduction (43.91%) were almost equal to the predicted ones (2.34 OD; 44.95%) as shown in Figure 3a and b, clearly proving the aptness of model.

Table 6. Precision of error between experimental and predicted data
S. no.Temperature (°C)pHInoculum size (OD)Predicted valueExperimental valuePrecision of error (%)
  1. a

    Data for biomass production

  2. b

    Data for cholesterol assimilation.

1.34.26.722.21a2.17a−3.6
2.35.06.7522.25a2.34a4.0
3.34.626.64243.91b44.95b2.3
4.34.06.75243.17b43.86b1.5
image

Figure 3. Two-dimensional contour plots showing (a) predicted biomass (cell density) and (b) predicted cholesterol removal with respect to pH and temperature.

Download figure to PowerPoint

DISCUSSION

  1. Top of page
  2. Abstract
  3. MATERIALS AND METHODS
  4. RESULTS
  5. DISCUSSION
  6. DISCLOSURE
  7. ACKNOWLEDGMENTS
  8. REFERENCES

Lactobacilli and bifidobacteria are two types of bacteria that are found in the gut and are considered probiotics because of their beneficial effects on health [26]. In our previous studies, we demonstrated bacteriocin production and its optimization in MRS and whey supplemented MRS medium, which enhance production by L. casei LA-1 [27, 28]. A probiotic strain of L. casei LA-1 isolated from non-dairy fermented food was selected as the probiotic for our previous studies [21]. The present study aimed to correlate reduction of cholesterol with cell growth in relation to physiological growth variables. The study implemented a two-step analysis, the first-step assessed the ability to deconjugate bile and the second-step evaluated and modeled various test variables for in vitro cholesterol reduction. Probiotics should be able to tolerate bile, not only for their viability in, and colonization of, the human gut but also because uptake of cholesterol occurs only when cultures are grown in the presence of bile [14]. Because deconjugation of bile acids to primary bile salts by BSH-positive bacteria leads to an increased demand for cholesterol from which bile salts are synthesized de novo in the liver, it may lead to decreased serum cholesterol concentrations. Interestingly, in a study of cholesterolemia in a tribe of Maasai [29], the serum cholesterol concentrations of Maasai men decreased after consumption of large amounts of milk fermented with a wild lactobacillus strain. Previous studies indicate that BSH-active organisms are most often isolated from the intestines or feces when the environment is rich in bile acids [30]. In our previous study, the isolate L. casei LA-1 isolated from a non-dairy fermented source was BSH positive and had strong deconjugation activity, which may be of considerable significance for its survival in the gut. Previous studies have reported correlations between removal of cholesterol and deconjugation of bile salts by L. casei [31] isolated from dairy products or of human origin. Removal of cholesterol by lactobacilli in vitro is due to an uptake or reduction of cholesterol by bacterial strains [15]. Later, researchers further demonstrated that some of the cholesterol assimilated by lactobacillus strains is incorporated into the cellular membrane [31-33]. Uptake of cholesterol by lactic acid bacteria and bifidobacteria is reportedly higher in mediums containing 0.4% ox gall [12].

In the present study, L. casei LA-1 strain was capable of removing cholesterol from the growth medium in the presence of bile salts, but the percentage of residual cholesterol in the culture medium varied considerably according to the organism's growth (Fig. 1). The pH of the medium was inversely proportional to growth of L. casei LA-1; that is, as growth increased, the pH of the medium decreased from 7.0 (initial pH) to 3.5. In addition, residual cholesterol in the culture medium also decreased. According to a previous report, cholesterol removal by L. acidophilus or other bacterial cells is caused by co-precipitation of cholesterol with deconjugated bile salts as the pH of the medium drops (<6) with increased acid production during growth [34]. These findings are similar to ours.

Further, we examined various growth-associated variables such as pH, temperature and inoculum size for their effects on in vitro cholesterol removal and biomass production using OFAT and found that all these factors have significant impacts on in vitro cholesterol removal and biomass production. Optimization by a conventional OFAT approach does lead to a substantial increase in biomass yield and cholesterol reduction; however, this is not only cumbersome and time consuming but also has the limitation of ignoring the importance of interactions between various variables. Therefore, we applied RSM for optimization of cholesterol reduction and biomass production using a five-level experimental design. Response surface analysis results indicated that inoculum size was the only one of the three variables studied that had a significant effect on in vitro cholesterol removal and biomass production by L. casei in the stationary phase of growth. The shapes of the contours indicated that mutual interaction effects between the test factors were not significant. That cholesterol removal correlates with inoculum size suggests that regulation of cholesterol reduction depends on the growth of the culture. Considering the purported mechanisms behind this phenomenon, it is rational to assume that some strains of lactic acid bacteria and bifidobacteria can remove cholesterol from culture medium during anaerobic growth in the presence of bile acids. Our findings suggest that the ability of L. casei LA-1 to assimilate cholesterol is highly dependent on its growth in each run, perhaps reflecting the growth of the inoculum used. This is in accordance with previous reports [35, 36]. We demonstrated that the ability of some strains of bifidobacteria to take up cholesterol into their cellular membranes is growth associated, because resting cells did not interact with cholesterol. Although our results with resting/dead cells can be correlated with previously reported results, there could be other mechanisms in addition to enzymatic deconjugation of bile acids by L. casei LA-1. These possibilities need to be confirmed in animal and human studies and the exact mechanism(s) of action of L. casei on cholesterol reduction elucidated in future work. Pereira and Gibson also reported that the ability of lactic acid bacteria and bifidobacteria to reduce cholesterol is highly dependent on their growth [12]. Response surface data from our in vitro study of cholesterol reduction in culture medium by L. casei showed maximum biomass production and cholesterol reduction at an inoculum size of 2.43 and pH 6.7. The quadratic effect of pH and temperature was also significant. When we examined cholesterol reduction as a response to inoculum size and initial pH as variables, we observed an enhancement in production at the upper axis. Finally, we developed and validated a regression model for growth and cholesterol reduction by probiotic L. casei.

Our findings on optimization and modeling of cholesterol reduction by a probiotic culture under in vitro conditions are important for fermentation processes for developing non-dairy probiotic foods. In future, trials need to be carried out on L. casei LA-1, so as it can be developed as a safe alternative therapeutic agent.

DISCLOSURE

  1. Top of page
  2. Abstract
  3. MATERIALS AND METHODS
  4. RESULTS
  5. DISCUSSION
  6. DISCLOSURE
  7. ACKNOWLEDGMENTS
  8. REFERENCES

None of the authors has any conflicts of interest associated with this study.

ACKNOWLEDGMENTS

  1. Top of page
  2. Abstract
  3. MATERIALS AND METHODS
  4. RESULTS
  5. DISCUSSION
  6. DISCLOSURE
  7. ACKNOWLEDGMENTS
  8. REFERENCES

The authors thank the Director, Thapar University, Patiala for providing adequate infrastructure and the Department of Biotechnology, Government of India for financial support.

REFERENCES

  1. Top of page
  2. Abstract
  3. MATERIALS AND METHODS
  4. RESULTS
  5. DISCUSSION
  6. DISCLOSURE
  7. ACKNOWLEDGMENTS
  8. REFERENCES
  • 1
    Manson J.E., Tosteson H., Ridker P.M., Satterfield S., Herbert P., O'Conner G.T. (1992) The primary prevention of myocardial infarction. N Engl J Med 326: 140616.
  • 2
    Metchnikoff E. (1908) The Prolongation of Life, 1st edn. New York: Putmans.
  • 3
    Nguyen T.D.T., Kang J.H., Lee M.S. (2007) Characterization of Lactobacillus plantarum PH04, a potential probiotic bacterium with cholesterol lowering effects. Int J Food Microbiol 113: 35861.
  • 4
    Park Y.H., Jong G.K., Young W.S., Sae H.K., Kwang Y.W. (2007) Effect of dietary inclusion of Lactobacillus acidophilus ATCC 43121 on cholesterol metabolism in rats. J Microbiol Biotechnol 17: 65562.
  • 5
    De Roos N.M., Katan M.B. (2000) Effects of probiotic bacteria on diarrhea. Lipid metabolism and carcinogenesis: a review of papers published between 1988 and 1998. Am J Clin Nutr 71: 40511.
  • 6
    Jin L.Z., Ho Y.W., Abdullah N., Jalaludin S. (1998) Growth performance. Intestinal microbial populations and serum cholesterol of broiler diets containing Lactobacillus cultures. Poultry Sci 77: 125965.
  • 7
    Kalavathy R., Abdullah N., Jalaludin S., Ho Y.W. (2003) Effects of Lactobacillus cultures on growth performance, abdominal fat deposition, serum lipids and weight of organs of broiler chickens. Br Poultry Sci 44: 13944.
  • 8
    Xu C.L., Ji C., Ma Q., Hao K., Jin Z.Y., Ki K. (2006) Effects of dried Bacillus subtilis culture on egg quality. Poultry Sci 85: 3648.
  • 9
    Tanaka H., Doesburg K., Iwasaki T., Mierau I. (1999) Screening of lactic acid bacteria for bile salt hydrolase activity. J Dairy Sci 82: 25305.
  • 10
    Ridlon J.M., Kang D.J., Hylemon P.B. (2006) Bile salt biotransformations by human intestinal bacteria. J Lipid Res 47: 24159.
  • 11
    Jones B.V., Begley M., Hill C., Gahan C.G.M., Marchesi J.R. (2008) Functional and comparative metagenomic analysis of bile salt hydrolase activity in the human gut microbiome. Proc Natl Acad Sci 105(13): 5805.
  • 12
    Pereira D.I.A., Gibson G.R. (2002) Cholesterol assimilation by lactic acid bacteria and bifidobacteria isolated from the human gut. Appl Environ Microbiol 68: 468993.
  • 13
    Ahn Y.T., Kim G.B., Lim K.S., Baek Y.T., Kim H.U. (2003) Deconjugation of bile salts by Lactobacillus acidophilus isolates. Int Dairy J 13: 30311.
  • 14
    Gilliland S.E., Nelson C.R., Maxwell C. (1985) Assimilation of cholesterol by Lactobacillus acidophilus. Appl Environ Microbiol 49: 37781.
  • 15
    USMAN (the United Graduate School of Agricultural Science), Hosono A. (1999) Bile tolerance, taurocholate deconjugation, and binding of cholesterol by Lactobacillus gasseri strains. J Dairy Sci 82: 2438.
  • 16
    Dambekodi P.C., Gilliland S.E. (1998) Incorporation of cholesterol into the cellular membrane of Bifidobacterium longum. J Dairy Sci 81: 181824.
  • 17
    Noh D.O., Kim S.H., Gilliland S.E. (1997) Incorporation of cholesterol into the cellular membrane of Lactobacillus acidophilus ATTCC 43121. J Dairy Sci 80: 310713.
  • 18
    Buck L.M., Gilliland S.E. (1994) Comparison of freshly isolated strains of Lactobacillus acidophilus of human intestinal origin for ability to assimilate cholesterol during growth. J Dairy Sci 77: 292533.
  • 19
    Montgomery D.C. (1996) Design and Analysis of Experiments. New York: John Wiley and Sons.
  • 20
    Lee S.L., Chen W.C. (1997) Optimization of medium composition for the production of glucosyltransferase by Aspergillus niger with response surface methodology. Enzyme Microb Tech 21: 43640.
  • 21
    Kumar M., Ghosh M., Ganguli A. (2011) Mitogenic response and probiotic characteristics of lactic acid bacteria isolated from indigenously pickled vegetables and fermented beverages. W J Microbiol Technol 28: 70311.
  • 22
    Du Toit, M., Franz, C.M.A.P., Dicks L.M., Schillinger U., Haberer P., Warlies B., Ahrens F., Holzapfel W.H. (1998) Characterisation and selection of probiotic lactobacilli for a preliminary minipig feeding trial and their effect on serum cholesterol levels, faeces pH and faeces moisture content. Int J Food Microbiol 40: 93104.
  • 23
    Rudel L.L., Morris M.D. (1973) Determination of cholesterol using o-phthalaldehyde. J Lipid Res 14: 364.
  • 24
    Myers R., Montgomery R.C. (2002) Response Surface Methodology: Process and Product Optimization using Designed Experiments. New York: Wiley.
  • 25
    De Boever P., Wouters R., Verschaeve L., Berckmans P., Schoeters G., Verstraete W. (2000) Protective effect of the bile salt hydrolase-active Lactobacillus reuteri against bile salt cytotoxicity. Appl Microbiol Biotechnol 53: 70914.
  • 26
    Mitsuoka T. (1998) The human gastrointestinal tract. In: Wood B.J.B., ed. The Lactic Acid Bacteria in Health and Disease. London: Elsevier Applied Science, vol 1, pp. 69114.
  • 27
    Kumar M., Jain A.K., Ghosh M., Ganguli A. (2012) Statistical optimization of physical parameters for enhanced bacteriocin production by L. casei. Biotechnol Biopro Eng 17: 60612.
  • 28
    Kumar M., Jain A.K., Ghosh M., Ganguli A. (2012) Industrial whey utilization as a medium supplement for biphasic growth and bacteriocin production by probiotic Lactobacillus casei LA-1. Prob Antimicrob Prot 4: 198207.
  • 29
    Mann G.V. (1974) Studies of a surfactant and cholesterolemia in the Maasai. Am J Clin Nutr 27: 4649.
  • 30
    Begley M., Hill C., Gahan C.G.M. (2006) Bile salt hydrolase activity in probiotics. Appl Environ Microbiol 72: 172938.
  • 31
    Liong M.T., Shah N.P. (2005) Acid and bile tolerance and cholesterol removal ability of lactobacilli strains. J Dairy Sci 88: 5566.
  • 32
    Noh D.O., Kim S.H., Gilliland S.E. (1997) Incorporation of cholesterol into the cellular membrane of Lactobacillus acidophilus ATCC 43121. J Dairy Sci 80: 310713.
  • 33
    Brashears M.M., Gilliland S.E., Buck L.M. (1998) Bile salt deconjugation and cholesterol removal from media by Lactobacillus casei. J Dairy Sci 81: 210310.
  • 34
    Klaver F.A.M., Van der Meer R. (1993) The assumed assimilation of cholesterol by lactobacilli and Bifidobacterium bifidium is due to their bile salt-deconjugating activity. Appl Environ Microbiol 59: 11204.
  • 35
    Tahri K., Crociani J., Ballongue J., Schneider F. (1995) Effects of three strains of bifidobacteria on cholesterol. Lett Appl Microbiol 21: 14951.
  • 36
    Tahri K., Grill J.P., Schneider F. (1996) Bifidobacteria strains' behavior toward cholesterol: coprecipitation with bile salts and assimilation. Curr Microbiol 33: 18793.